Volume 6, Issue 2

ollision C in

2011 Vol. 6 Iss.2

D !

DV ta I Da CS est C- h T A R C ra s 11 ing 20 clud

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The International Compendium for Crash Research

Volume 6 Issue 2

Tired of using complicated software to handle your point clouds?

Visual Statement proudly introduces EdgeFX Point Cloud Edition – the newest product in the FX software line. Intuitive and easy to use, this powerful tool was built specifically for accident and crime scene reconstructionists who are using 3D Laser Scanner technology.

Collision: The International Compendium for Crash Research

INTRODUCING EDGEFX POINT CLOUD EDITION

Fall 2011

USe OF eDR dATA IN vEHICLE aCCIDeNT reCONSTRUCTION

· “Revisit” a scene in 3D at any time with full color, high resolution detail.

· Easily place models by dragging the object within the 3D scene.

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Volume 6, Issue 2 - FAll 2011

· Accurately measure distances in seconds and locate important evidence points from the comfort of your own office.

intersection cRASH RecONSTRUCTION Plus Articles from the

ECCENTRIC COLLISIONS AND POST--IMPACT MOTION APPLICATIONS OF gps IN COLLISION RECONSTRUCTION www.collisionpublishing.com

Crash site evidenCe

A 2010 Chevrolet Equinox SUV attempted to make a left turn in front of a 2003 Dodge Ram pickup. The pickup was in the middle northbound lane when it struck the left-rear side of the SUV, causing both vehicles to rotate CCW to their final rest positions.

The right-rear passenger in the SUV suffered significant facial injury, but there was no physical evidence on the back of the right front seat. How did the facial injury occur?

For more information on the capabilities of HVE please visit edccorp.com

HVE directly answers the following questions using Newton’s laws of motion:

Questions

Answers

Impact Speeds

SUV: 22 – 25 mph Pickup: 42 – 45 mph

Peak Impact Force

SUV: Fx= -37,850 lb, Fy= 66,350 lb, Fz= -1,560 lb Pickup: Fx= -71,400 lb, Fy= -26,700 lb, Fz= 1,880 lb

Peak Impact Acceleration

SUV: 18 – 23 g Pickup: 12 – 15 g

Peak Angular Velocity

SUV:

~ -340 deg/sec

PDOF

SUV:

~ -61 deg

Occupant Analysis (Right-Rear)

Seat Belt Status: Unbelted General Motion of Occupant: Left/Forward Facial Contact Detected: Left Front Seat Headrest

Required Technologies

SIMON 3-D Vehicle Dynamics Simulation Model DyMESH 3-D Collision Model GATB 3-D Occupant/Pedestrian Simulation Model

Other software may claim to answer these questions. Have you closely evaluated their claims and the basis for their results?

To learn more about HVE and all of the available tools for crash investigators, call 503.644.4500 or visit www.edccorp.com. Our professional sales staff will help you get started using HVE today!

Knowledge = Power 7096-0820

Engineering Dynamics Company, LLC • 550M Ritchie Hwy #128, Severna Park, MD 21146 USA • Phone 503.644.4500 • www.edccorp.com

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Supporting Windows 7 tablets and Windows Mobile devices, EVR allows you to experience the power, precision and productivity gains associated with being able to visually verify your ongoing field evidence collection. EVR now utilizes high definition graphics, great for all display types.

PointCloud 2010

MapScenes Forensic CAD is the most precise desktop forensic mapping software available in the world. This powerful and feature rich program provides law enforcement professionals and accident reconstruction specialists, like you, with confidence that the evidence they present is precise, compelling and irrefutable.

Built on the MapScenes Forensic CAD platform, MapScenes Capture is a full featured forensic animation product built for anyone wanting to create 2D and 3D animations. Capture is the only product available that truly gives you the flexibility and power you need to accurately animate your scenes.

www.MapScenes.com 1.800.668.3312

MapScenes PointCloud is a powerful point cloud / LIDAR data visualization and animation tool built on the MapScenes Capture platform. Forensic investigators and accident scene reconstructionists use the point cloud capabilities along-side the mapping and animating features. Use point cloud data for faster scene mapping AND to enhance your animation for spectacular results!

and MicroSurvey are Registered in the U.S. Patent and Trademark Office ® MapScenes All other brand names, product names or trademarks are property of their respective owners.

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Articles & Case Studies Where contributors can share and comment on recent writings.

Training Calendar Moderated by certified MapScenes trainers.

User Gallery View sample maps & diagrams or animations created with MapScenes, by professionals.

Collision Investigation Solutions

MapScenes® is Registered with the U.S. Patent and Trademark Office by MicroSurvey Software Inc.

Contents inside

Fall 2011

Volume 6 Issue 2

4

Letter From the Editor

8

NAPARS: Letter From the President

12

Training Calendar

16

Crash and Burn 2011

18

ARC-CSI Crash Conference Data DVD

114

Book Reviews

20

opinion 14

Crash Testing... Why Bother?

118

Peer Reviewed Papers, the SAE and Collision Magazine Mutually Exclusive Concepts?

34

by W.R. Rusty Haight

by W.R. Rusty Haight 102

My Turn At the Wheel: The Mathematics of a Bicycle Going Down an Incline

by Peter Bergh

features 20

A Short History of Nearly Everything! ( … about McHenry and Computers in Highway Safety)

46

by Brian McHenry 34

ARC-CSI Crash Team Boot Camp Experience and Crash Test Data Review

by ARC-CSI Boot Camp Team 46

Intersection Crash Reconstruction - From Cradle to Grave

by Terry D. Day 56

Applications of GPS Data in Collision Reconstruction

68

Accident Reconstruction Photogrammetry Using Zoomed Images from Digital Cameras

by Daniel Melcher, Jay Przybyla, Rachel Keller, Thomas Rush

102

by Lee DeChant, J Rolly Kinney 78

The Use of EDR Data in Vehicle Accident Reconstructions

by Raymond Brach 88

Fundamentals of Highway and Roadside Design for the Accident Reconstruction Specialist

by Francisco Klein 108

Eccentric Collisions and Post-Impact Motion - Busting a Myth

by Bruno Schmidt, Michelle Beach www.collisionpublishing.com

Collision Magazine 3

Letter from the editor They say things happen for a reason. Collision came about that way, if you would have asked us 7 years ago if we were planning a magazine, I would have answered “no,” but here we are. Since the last issue of Collision, there have been many changes in crash reconstruction generally and within the Collision family specifically. For example, this issue commemorates the 10th Anniversary of the ARC-CSI Crash Conference which was one of the best crash conferences we’ve hosted yet. Moreover, it included more crash tests with newer cars (one a 2011 model year vehicle), a revitalized crash test crew, the addition of the Crash Team Boot Camp opportunity as well as the use of a new area at the Las Vegas Motor Speedway which provided (and will provide in the future) new and exciting opportunities for testing and more.

As this issue goes to print, we have secured dates and contracts for the 2012 CDR User’s Summit in Houston which will feature new and exciting announcements from Bosch addressing newly signed manufacturers as well as up-to-the-moment CDR System coverage and more.

The 2012 ARC-CSI Conference has also been scheduled for June 4-7, 2012 and we are currently in the planning stages. This past year, when we announced the Crash Team Boot Camp opportunity, the limited number of seats sold out inside of 72 hrs! We will offer the Boot Camp again in 2012 and, given the feedback we’ve received thus far, anticipate another full house next June. The Crash Team Boot Camp participants prepared two articles found in this issues of Collision; one on the data analysis of their crash test and the other on the experience itself. It’s clear they had fun, learned something and came away better for the experience. We already have some of the cars in place for the testing in 2012 thanks to new sponsors like the Las Vegas Metropolitan Police and the Nevada Highway Patrol.

In addition, plans are in motion to tie in an insurance industry conference immediately following the ARC-CSI Crash Conference. This new conference, named Collision Claims Expo, will make for a larger and more “opportunity rich environment” for all.

As things change, another evolution in the industry was the suspension of the Accident Investigation and Reconstruction Practices Committee by the parent organization, the International Society of Automotive Engineers. This longstanding and widely recognized committee has been the primary if not lone activity at the SAE dedicated to crash analysis and reconstruction for years and members have contributed to the larger crash reconstruction knowledge base in a number of ways from SAE papers to articles in Collision and more. A copy of the suspension letter is reprinted in this issue on page 6.

When one looks at the rationale for the suspension, it’s hard to imagine how the committee can be rebuilt to meet the requirements set out in the reasons behind the suspension, but everyone here at Collision wishes them well.

With that being said, the SAE’s suspension of the AIRP Committee gave birth to a new round of discussion regarding peer review of papers in the crash reconstruction field and there not being such a process in place in Collision. In this issue, there is a another discussion of peer review (pages 112-113) and the Collision magazine approach to distribution of information within the community.

So I leave you to dive in to yet another jam-packed issue of Collision Magazine. I look forward to seeing you in Houston at the 2012 CDR User’s Summit.

Managing Editor

4

Collision Magazine

www.collisionpublishing.com

BACK ISSUES

Collision Publishing LLC PO Box 3383 Kirkland, WA 98083-3383 Toll Free: 800-280-7940 Email: editor@collisionpublishing.com Web: www.collisionpublishing.com ISSN: 1934-8681

COLLISION STAFF Scott Baker Sean Haight Tonya Baker Carla McLeod

Owner, Managing Editor Senior Editor Advertising Manager Subscription Services

All rights reserved, © 2006-11 Collision Publishing LLC. The opinions and conclusions expressed in this publication and attached data disk and throughout the articles attributed to specific authors are the opinions and conclusions of the authors noted and not necessarily the editorial staff or anyone else for that matter. While some articles have been reviewed for content, the accuracy of reprinted models or equations cannot be fully guaranteed. It is the responsibility of the reader to apply critical thinking to an individual review of the content and make their own personal judgements as to its value to them, individually.

At the end of the day, facts belong to everybody, any other opinions to us. The distinction is yours to draw...otherwise, the opinions expressed herein are not necessarily those of any employer, not necessarily ours and probably not necessary. Dissenting opinions, discussion or conclusions which may

express an adverse position to those expressed herein by specifically cited authors can be addressed in writing by sending an email to the editor at editor@collisionpublishing.com or sending a “regular mail” letter to us at PO Box 3383, Kirkland, WA 98083-3383. By sending correspondence to either our email or snail mail

addresses listed in this publication you are agreeing that: (1) we are by definition, “the intended recipient” (2) all information in the email is ours to do with as we see fit and make such financial profit, political mileage, or good joke as it lends itself to and, (3) this overrides any disclaimer or statement of confidentiality that may be included on your original message. The entire physical universe, including this publication and attached data disk, may one day collapse back into an infinitesimally small space. Should another universe subsequently reemerge, the existence of this publication and data disk in that universe cannot be guaranteed.

SUBMIT AN ARTICLE If you would like to submit an article to be published in Collision please email us your article for review or call us toll free 800-280-7940. Email: editor@collisionpublishing.com

ADVERTISING RATES & INFO If you would like to advertise your products or services in Collision Magazine, rates, availability and other information are available online at: www.collisionpublishing.com www.collisionpublishing.com

If you would like purchase back issues of Collision Magazine, please visit www.collisionpublishing.com or call us toll free 800-280-7940.

ADVERTISER INDEX

PAGE

4N6XPRT Systems Inside Back, 120 ARAS360 33 ARC-CSI Crash Conference 18 CDR Training 45 CDR User's Summit 13 Collision Claims Expo 11 Collision Publishing 117 Collision Safety Institute 101 Crash Data Group (CDR) 55, 100 CrashTest-Service.com 116 Engineering Dynamics Inside Front, 54 Eos Systems: Photomodeler 67 iWitness 77 MapScenes 1, 2, 63-66 NAPARS 8 Northwestern University 10 Vericom Computers 113 Visual Statement 87,107, Back

Included with this issue of Collision

is the 2011 ARC-CSI Crash Conference data DVD. The ARC-CSI DVD includes all the photos, video, instrumented crash testing data, scaled diagrams, speaker Power Points, and any other supporting data compiled in a easy to review, menu-driven data DVD.

Next ARC-CSI Crash Conference June 4-7, 2012 www.crashconferences.com Collision Magazine 5

6

Collision Magazine

www.collisionpublishing.com

Editors’ note: As referenced in the Letter from the Editor and elsewhere in this issue, the significance of the suspension of this longstanding SAE committee cannot be understated and after weighing the potential that some may consider reprinting this letter in some way inflammatory, in the interest of full disclosure and in the context of the impact it has or may have on a segment of the community, readers of Collision and at least the perception of literature in the community in general, we thought the information, reprinted here as it was originally disseminated, was important enough to include in this issue.

www.collisionpublishing.com

Collision Magazine 7

Premier Industry Partner Letter from the President

I recently assisted a local police group with a crash investigation where a late model car traveled completely left of center, sideswiped two oncoming vehicles before finally crashing head-on into a truck.

The damage to the car was quite severe and the driver was fatally injured. The investigation was centered on the obvious question, “Why did the car travel and remain left of center?” Fortunately in this case the car was equipped with a factory Event Data Recorder (EDR) in the airbag system which although badly damaged, was painstakingly repaired so that it could be downloaded. The EDR recorded details on four separate impact events during the crash, complete with pre-crash driver inputs that allowed for a com-

prehensive analysis of the entire chain of events. The data supported a conclusion that the crash was likely caused when the driver suffered a seizure or other medical disorder.

This case is yet another reminder of how far we have come in our field, to a time when one cannot possibly be an expert in all facets of crash investigation or reconstruction. In some cases we will have need for advice or assistance from experts in various specialties, such as tire failure, human factors, perception/reaction, visibility, heavy truck EDR…. the list goes on. And there is nothing better than having a friend or colleague with specialized knowledge that you can turn to for advice or as a peer review for your thoughts and ideas. Where is the best place to find those friends and colleagues? The quickest way is to become active in a professional organization within your field. Through training events and conferences, magazines, newsletters, and our web site, NAPARS strives to connect our membership and promote information sharing as well as friendship. NAPARS enjoys a diverse membership, many of whom are well known experts in the specialized fields of accident reconstruction.

To our members, I invite you to become more active in our association’s various activities, discussions, and training opportunities. And to prospective members, I invite you to join us and make some new friends. As Benjamin Franklin put it, “An investment in knowledge pays the best interest.”

Chuck Veppert President, NAPARS

The National Association of Professional Accident Reconstruction Specialists is a non-profit organization whose members have joined together to share the challenge of dealing with the complex problems of accident reconstruction and to upgrade and ultimately professionalize the accident reconstruction field.

8

Collision Magazine

www.collisionpublishing.com

www.napars.org

Industry Partners IAARS is one of the oldest associations dedicated to

expanding the knowledge and training of accident reconstructionists. Formed in 1980, we have members from several different countries as well as many different states across the U.S. We have three levels of membership. Our highest level, Fellow, includes a peer review of a reconstruction project. This peer review feature can be very beneficial to a member seeking expert witness qualification in court. One of the criteria a judge can consider when deciding if a person qualifies as an expert is a peer review of his or her work. We offer opportunities for a member to publish work or research in the field of accident reconstruction. This, also, can be very important when qualifying as an expert witness in court proceedings.

Membership in IAARS has other advantages, including a dis-

ASPACI is a non-profit society whose members have

joined to share in the challenge of analysing the complicated issues of road collision investigation.

ASPACI was formed in 1991 by a group of police and collision reconstructionists who felt there was a need for information sharing between police and associated institutions in the Australia, South East Asia, New Zealand and South Pacific area.

Its primary function is to assist in the spreading of knowledge and enhancing expertise in the science. The Association seeks to promote a professional approach to collision investigation and to encourage the highest standard of ethics, integrity and honesty among its members.

The ARC Network

was founded in 1998 and since has grown to be the largest and most respected organization for Accident Reconstruction and Traffic Investigation.

The ARC Network is more than just an organization it is a research and communications Internet portal for everything accident reconstruction. The ARC Network provides research tools, Expert directory, event calendar, industry news feeds, education directlory and a Member's Only area that gives access to various online databases and information.

count (from IAARS) on a subscription to Collision Magazine, member discounts at our training seminars and others listed on our web page, www.iaars.org.

We have annual training opportunities at different locations across the country. We try to have some sort of actual vehicle testing at each seminar, including full scale vehicle crashes. As a member, you would have access to a vast archive of results from many different and sometimes quite unique tests.

Sincerely, Dan Lofgren President, IAARS www.iaars.org The early days saw the number of members vary with the base of the association in Victoria, Australia. ASPACI became ASPACI Incorporated in 1993 in Victoria. Now we boast members from all over mainland Australia, New Zealand., United Kingdom, and the United States, as well as parts of Asia.

Membership to ASPACI is open to all persons engaged in collision investigation and its allied fields. The association members include Engineers, Police Officers, Independent Consultants, Scientists, Insurance Corporations, Manufacturers and Safety personnel. ASPACI is not a Trade Association or Political Lobby group, nor is it a Police organisation.

User's Summit and a free copy of Greg Russell's Excel Crush Stiffness spreadsheet program. Extend your savings and sign up as a Police Agency member or Platinum member and receive a complimentary subscription to Collision Magazine!

In addition, as a member you have the choice of being listed in the most-visited Expert Directory on the Internet. Our Expert directory boasts a #1 ranking in Google searches (a feat worth much more than the cost of membership)!

The ARC Network offers various membership levels to fit your needs and budget. Membership starts at just $79.00 per year.

However, that is where the value of the ARC Network starts.

With your membership you not only get access to everything in the ARC Network, you also receive a, $50 discount to the annual ARC-CSI Crash Conference, a $50 discount to the CDR

Scott Baker President The ARC Network (800) 280-7940 www.accidentreconstruction.com arc@accidentreconstruction.com

For information on becoming a Collision Industry Partner send an email - editor@collisionpublishing.com www.collisionpublishing.com

Collision Magazine 9

ADVANCING EXCELLENCE IN PUBLIC SAFETY For 75 years, the Northwestern University Center for Public Safety has provided professional development to law enforcement professionals throughout the United States and abroad. NUCPS offers the world-renowned School of Police Staff and Command, as well as courses and programs in police management, police operations, police motorcycle operator and instructor training, crime scene investigation and forensics, crash investigation, transportation engineering and more.

nucps.northwestern.edu/collision nucps@northwestern.edu • 800-323-4011

Crash Investigation and Reconstruction

Fall 2011–Spring 2012 Course Schedule

The concept of scientific crash investigation has been a part of the Northwestern University Center for Public Safety (NUCPS) since its inception in 1936.

We literally wrote the book on crash investigation and reconstruction. In addition to writing the books, we continue to be world leaders in providing training in traffic crash investigation and reconstruction through our many courses of study.

We offer the most comprehensive program of its kind, with the course series beginning at basic crash investigation and culminating in advanced traffic crash reconstruction.

Unless otherwise noted, all classes will be held at NUCPS’s state-of-the-art facilities on the Northwestern University campus in Evanston, Illinois. For an up-to-date listing of crash investigation and reconstruction courses scheduled on campus and throughout the country, please visit nucps.northwestern.edu/collision.

ONLINE

March 5–9, 2012

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March 12–23, 2012

Crash Investigation 2

March 26–April 6, 2012

Math and Physics Workshop for Crash Reconstruction April 9–13, 2012

April 16–20, 2012

Traffic Crash Reconstruction 1 November 16, 2011 May 24, 2012

Register now for any on-campus course and select webinars and save 20% on subsequent registrations from the same agency for the same course.

Crash Investigation 1

Vehicle Dynamics

EVANSTON, ILLINOIS CDR Technician Level 1*

* Register for CDRT1 and CDRT2 at the same time and save $25.

Advanced Crash Reconstruction — Utilizing Human Factors Research

CDR Technician Level 2* November 17, 2011 May 25, 2012

NEW — Traffic Crash Reconstruction 3 February 27–March 2, 2012

April 23–May 4, 2012

Traffic Crash Reconstruction 2 May 7–11, 2012

Heavy Vehicle Crash Reconstruction May 14–18, 2012

Pedestrian Vehicle Crash Reconstruction May 21–23, 2012

Traffic Crash Reconstruction Refresher May 30–June 1, 2012

NOW AVAILABLE FROM NORTHWESTERN UNIVERSITY CENTER FOR PUBLIC SAFETY

TRAFFIC CRASH RECONSTRUCTION,

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Purchase your copy today. Spend a total of $500 or more and receive a 5% discount. nucps.northwestern.edu/tcrbook 800-323-4011, extension 1-5670

training calendar for Accident Reconstruction and Traffic Investigation COLLISION PUBLISHING www.collisionpublishing.com Date

Course

Location

Date

Course

Location

1/16-18/2012

CDR Summit

Houston, TX

7/4-7/2012

ARC-CSI Crash Conf.

Las Vegas, NV

1/19/2012

CDR Train the Trainer

Houston, TX

7/7-9/2012

Collision Claims Expo

Las Vegas, NV

7/2-7/2012

ARC-CSI Boot Camp

Las Vegas, NV

COLLISION SAFETY INSTITUTE www.collisionsafety.net Date

Course

Location

Date

Course

Location

2/6-10/2012

CDR Analyst

Henderson, NV

3/5-9/2012

CDR Analyst

Baton Rouge, LA

2/13-17/2012

CDR Analyst

Worcester, MA

4/16-20/2012

CDR Analyst

Arlington, TX

ENGINEERING DYNAMICS CORPORATION www.edccorp.com Date

Course

Location

Date

Course

Location

1/23-27/2012

EDC Reconstruction

Burbank, CA

2/27-3/3/2012

HVE Forum

New Orleans, LA Location

FACTUALDIAGRAMS.COM www.factualdiagrams.com Date

Course

Location

Date

Course

1/30-2/2/2012

ACTAR Test Prep.

N. Las Vegas, NV

2/20-24/2012

Diagramming with Fontana, CA Crash Zone/Crime Zone

NORTHWESTERN UNIVERSITY CENTER FOR PUBLIC SAFETY nucps.northwestern.edu Date

Course

Location

Date

Course

Location

5/24/2012

CDR Tech. Level 1

Evanston, IL

3/12-23/2012

Crash Investigation 1

Evanston, IL

5/25/2012

CDR Tech. Level 2

Evanston, IL

3/26-4/6/2012

Crash Investigation 2

Evanston, IL

2/22-3/2/2012

Traffic Crash Recon. 3

Evanston, IL

4/16-20/2012

Vehicle Dynamics

Evanston, IL

3/5-9/2012

Adv. Crash Recon - Uti- Evanston, IL lizing Human Factors Research

4/9-13/2012

Math & Physics Workshop for Crash Reconstruction

Evanston, IL

5/14-18/2012

Heavy Vehicle Crash Reconstruction

Evanston, IL

5/21-23/2012

Pedestrian Vehicle Crash Reconstruction

Evanston, IL

4/23-5/4/2012

Traffic Crash Recon. 1

Evanston, IL

5/7-11/2012

Traffic Crash Recon. 2

Evanston, IL

5/30-6/1/2012

Traffic Crash Reconstructon Refresher

Evanston, IL

ANY TIME

Crash Investigation 1 Online

N/A

ANY TIME

Crash Investigation 2 Online

N/A

1/9-3/30/2012

Crash Investigation 1 Online

Instructor-led

1/9-3/30/2012

Crash Investigation 2 Online

Instructor-led

VISUAL STATEMENT www.visualstatement.com Date

Course

Location

Date

Course

Location

1/9-12/2012

FX3 w/ Total Station

Roseville, CA

1/23-25/2012

FX3 Advanced Diagramming

Upland, CA

WeCARE www.rudydegger.com Date

Course

Location

Date

Course

Location

1/9-12/2012

Basic Traffic Collision Investigation

Concord, CA

6/18-29/2012

Adv. Traffic Collision Investigation

Concord, CA

2/27-3/1/2012

Basic Traffic Collision Investigation

Concord, CA

3/12-23/2012

Traffic Collision Reconstruction Level 1

Concord, CA

4/24-27/2012

Basic Traffic Collision Investigation

Concord, CA

5/21-25/2012

Traffic Collision Inv. Intermediate - Skidmarks

Concord, CA

1/30-2/3/2012

Traffic Collision Inv. In- Concord, CA termediate - Skidmarks

If you would like to list an upcoming course or event in Collision Magazine, please email editor@collisionpublishing.com

The annual Crash Data Retrieval User's Summit is a comprehensive training experience designed to expand the knowledge of those using the Bosch CDR System or those who are involved in the collection and analysis of motor vehicle crash data. The topics at the Summit address user applications, case studies, legal issues, legislation and future product development. Subject matter experts from around the globe will present on the latest topics and freshest research as it pertains to crash data retrieval and the expanding field of event data recorder functionality.

2012 Topics & Speakers • Chip Swapping: Risk v. Reward, by David M. Little, P.Eng. • CDR Data From More Than One Car: Fitting it Together, by Ray Wangler • Frye/Daubert and the Admission of Expert Testimony, by Thomas L. Bohan • Comparison of Toyota ROT and Bosch CDR Data, by Kent Boots • A Comparison of Raw Data in ECUs Versus Data Found in CDR Reports and its Effects on CDR Analysis Integrity, by William Rosenbluth • Using the Monte Carlo Method with Crash Event Data, by Roger W. Barrette • RCM, PCM, RDS... Just Acronyms or A Lot More?, by W.R. "Rusty" Haight • CDR Admission and Expert Preparation, by William Melkonian • Is a Search Warrant Required? Case Law Review, by Chuck Gillingham • BREAKOUT SESSION: Backpowering a Vehicle to Image Crash Data • BREAKOUT SEESION: RCM and PCM Data Together • BREAKOUT SESSION: Mock CDR Admissibility Hearing • BREAKOUT SESSION: Downloading Non-supported Vehicles ... more topics to be added soon

n o i n i p O

A few years ago I read an advert for a conference in the USA. The author proclaimed, “To [sic] many collisions have already been staged and we kind of have that sort of analysis figured out so we wanted to do something that means something to the investigator… be it law enforcement or private.”

Crash Testing...

Why Bother?

Reprinted from:

"Crashtest Technology International"

September 2011

SEPTEMBER 2011

Thomas Broberg As rivals catch up with Volvo safety standards, the company’s senior technical advisor reveals his plans for the future

ATDs

Meet the newest, smartest generation of crash test dummies yet

New standards

The aftermath of the Williamson vs Mazda decision has major implications for crash test engineers, as Byron Bloch discusses

Electric vehicles What does this growing technology mean for crash test labs?

14

The future of labs?

Crash Test Zone

Experts reveal their visions of the crash lab of 2025

See the latest generation of crash test technology at Automotive Testing Expo North America

Collision Magazine

Grammatical issues notwithstanding, I had to ask myself: Too many? Could that be the case?

Have we reached a point where crash tests didn’t mean anything to the crash investigator anymore?

Automobile crash testing has a long and storied history. Mercedes-Benz, for example, conducted its first crash tests in September 1959, and there have been many tens of thousands conducted since then. So, when did we get to the point where they weren’t meaningful anymore? Over the course of the last 22 years, I’ve been involved in more than 1,300 crash tests and I’ve driven in more than 951 of those myself, but apparently there’s someone out there that believes, ‘well, we’re done, we’ve learned all we can, let’s go do something else’.

Well, I have to say, not so fast. First, we have to ask ourselves, why do we conduct crash tests? Going back to at least the 1950s, crash testing has become universally recognized as a reliable tool for optimizing and testing safety features. In addition to the safety research and improvement aspect, government agencies use it to evaluate the need for regulation or to support regulatory decisions. Myself and others use crash tests as the ultimate teaching lab… but have we got that analysis figured out?

I don’t think so, no. With each new model year, the many systems that make up a car as a whole change and, as they do, there has to be some sort of evaluation of the systems and components that make up those systems. As it relates to safety and, to a degree, performance considerations such as crashworthiness, the best way to see how something will perform is to, well, crash it. It’s called a ‘test’ for a reason…

Testing components individually precedes the full-scale crash test, but there’s really no practical substitute today for taking a car out and subjecting it to the conditions it may encounter in the real world by running a crash test. Many organizations and entities are

www.collisionpublishing.com

working on crash test simulations, which, in the long term, hold the promise of being less expensive and less timeconsuming, but that’s not the case today.

The National Crash Analysis Center (NCAC) at George Washington University in the USA, for example, has a cutting edge simulation lab where the researchers are painstakingly modeling the many hundreds of individual components of a given car – a process that can take years in some cases – then the finite element modeling ‘crash test’ can be conducted over and over in a number of different configurations or scenarios. But the basis for the reliability of that sort of testing, the foundation for the notion that such a simulation can be a useful tool is: the crash test, the fullscale, car-into-something instrumented and documented test.

“Apparently someone out there believes, ‘well, we’re done, we’ve learned all we can, let’s go do something else’. Well, I have to say, not so fast”

Beyond the labs such as found at NCAC, we see publicly available simulation programs such as MADYMO Solver and human and crash dummy models, which, again, are derived from experience gleaned from full scale, instrumented crash tests. While simulation systems such as MADYMO Solver are more cost-effective and demonstrably less timeconsuming today than they were in the past, there’s still the need to actually put metalto-metal (or brick) and see how the systems behave, and then use that information to improve on whatever simulation system is on the horizon.

Some 52 years after its first crash tests, Mercedes-Benz runs about two tests a day today, and is building onto its crash facility because it needs additional space for more varied tests. The company wants to continue to learn from what is still the best lab out there for understanding how cars and bodies behave in a crash: the crash test. While we might have the analysis figured out, we can and should continue to learn by crashing. >> W. R. ‘Rusty’ Haight is director of The Collision Safety Institute, an independent traffic collision research, training and consulting organization that operates mainly in the USA, Canada and Australasia. He can be contacted via www.collisionsafety.net See Rusty and his crash crew at the 2012 ARC-CSI Crash Conference June 4-7, 2012 - Las Vegas, NV www.arccsi.com www.collisionpublishing.com

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he Governing Board of the New England Association of Insurance Fraud Investigators (NEAIFI) together with CEMLEC, the Central Massachusetts Law Enforcement Council Accident Reconstruction Team, organized a first-of-its-kind educational opportunity for insurance and law enforcement professionals as well as prosecutors from all over Massachusetts and the greater New England region in May 2011.

The Grafton Mass police coordinated with the Wyman Gordon Company to secure a location for a series of crash tests and a controlled car burn held in front of nearly 200 on lookers. Grafton Chief of Police Normand A. Crepeau, Jr. and Mendon, Mass Police & Fire Chief Ernest Horn arranged for sufficient public safety personnel for the crashes and car burn demonstration. Liddell Brothers Contractors installed guardrails and safety bar-

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riers which were used as part of the interesting series of crash tests which included guard rail climb/shallow impacts and tire blowouts. Allen Davie, of Karcraft in Uxbridge, MA provided mechanical assistance and expertise and Direnzo Towing in Millbury, MA provided towing assistance. Several auto insurance carriers donated cars to crash including MAPFRE USA (Commerce Insurance), Liberty Mutual, Progressive, Met Life Home & Auto, and Plymouth Rock Assurance.

The 2011 event was coordinated and sponsored by NEAIFI, CEMLEC, MAPFRE, USA, the National Insurance Crime Bureau (NICB), Smith & Brink, PC, The Crash Data Group, and Robert Bosch, LLC. The data from the 8 crash tests and the data reduction to a disk distributed after the single day event to those in attendance was coordinated by the Collision Safety Institute.

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Another training opportunity coming in 2012!

Don't miss the Collision Claims Expo coming to Las Vegas in June 2012. This specialized 3-day expo will provide invaluable information and training in the area of insurance claims, vehicle accidents and crash data collection. www.collisionclaimsexpo www.collisionpublishing.com.com

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ARC-CSI 2011 DVD Pre-crash prep day included a series of Toyota "EDR" tests, and instrumented "low closing speed"/low delta-V tests. Crash day at the track featured 7 crash tests with a top closing speed of 54 mph (87 km/h).

The conference data DVD was distributed to all attendees and vendors and is also included in this issue of Collision, some of what you will find on the DVD: • • • • • • • •

Over 50 video clips Over 720 photos CDR files Toyota "ROT" files Accelerometer data Vehicle data files Speaker PowerPoint presentations Scene/vehicle/crash diagrams and more...

Join us next year for the 2012 ARC-CSI Crash Conference June 4-7, 2012 Las Vegas, NV www.arccsi.com 18

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May 2011 marked the 10th anniversary of the ARC-CSI Crash Conference. A new location at the Las Vegas Motor Speedway, a revamped crash test crew and a wide variety of newer model year vehicles made this one of the best crash conferences to date. Moving to a new area at the Las Vegas Motor Speedway made for new options and opportunities for different testing configurations.

The crash crew, including a newly redesigned user and observer friendly remote drive system, made for a wide variety of crashes from lower speed to much higher impact speed and higher delta-V tests.

This year also marked the first ARC-CSI Crash Team Boot Camp. Two articles are included by the Crash Team Boot Camp members in this issue. Mark your calendar (June 4-7, 2012) for another amazing year at the ARC-CSI Crash Conference and another opportunity to participate in the Boot Camp Experience!

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A Short History of Nearly Everything! ( … about McHenry and Computers in Highway Safety)

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n his 2005 book A Short History of Nearly Everything, Bill Bryson takes readers on a spirited journey from the Big Bang to the present day with all things scientific in between. The size of the universe, the creation of the earth, Teutonic plates, tornados, cosmology, astronomy, paleontology, geology, physics, the garden club?, it’s all in the book. You will also find some very interesting stories about the many people involved in scientific discovery throughout the ages. I highly recommend the book as you will certainly enjoy the read!

McHenry in highway safety. I will focus in particular on some of the pioneering accomplishments in the field of computer applications to highway safety by my father, Raymond R. McHenry in his first 25+ years in the field. I’ll also present some of the things he and I have accomplished working together for the past 30+ years as well as what we are planning for the future.

The journey into the field of highway safety for Ray McHenry started in the 1950’s. Fresh from WWII Air Force military service and graduating from the In the same spirit of things, this article will take you University of Maine in Engineering Physics, he took from the Big Bang of the 60’s digital computer revo- a job in the automobile industry in Detroit, MI. He lution to the present time with all things related to started with Chrysler (which included attending and 20

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Brian G. McHenry McHenry Software, Inc. ARAS 360 Technologies Inc.

graduating from the Chrysler Institute) and then moved to Ford. Around 1960 he decided that he’d had enough of research exercises related to product development. The straw that broke his spirit’s back was that after spending an extended and successful effort working on a revolutionary hydro-pneumatic suspension design and implementation, the prototype vehicle was destroyed and the project filed for potential future interest because the ‘suits’, aka the marketing department, didn’t think it would sell in the existing market. It was then that Ray decided that it was time to pursue a different type of engineering

work. Around 1960 he took a job in the transportation research department at Calspan (then known as Cornell Aeronautical Lab) in Buffalo, New York.

One of the first projects at Calspan which utilized Ray’s unique analytical skills was related to occupant kinematics. In 1963 the U.S. Public Health Service and the Automobile Manufacturer’s Association, Inc. funded research at Calspan performed by Ray to develop a response to a Consumer Reports issue [1] and related reports [2, 3] that included the assertion that American

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seat belts failed under the Swedish test conditions and "the major points of failure of the belts tested were the webbing…and the floor brackets themselves".

As part of the research Ray McHenry and his team at Calspan created an occupant simulation model for longitudinal collisions to assist in the investigation and understanding of the differences between US and European belt standards. The resulting computer program was called the CAL-2D [4]. The program represented one of the first computer simulation applications created and utilized in the field of highway safety research.

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AL-2D – Occupant Simulation The CAL-2D model was created "in order to help improve understanding of the complex relationships of forceacceleration-time-position-velocity that occur in the impact and energy-absorbing cycle of automobile passenger restraint systems". The study was performed to provide guidance concerning "(1) fundamental differences in the results obtained by static and dynamic testing and (2) the possible need for dynamic acceptance testing of seat belts.

Figure 1: CAL-2D Mathematical model of human body and restraint system on test cart (11 degrees of freedom)

One of the results of the study was the conclusion that "the use of a very short stopping distance in a dynamic cart test of lap belts can produce a distorted comparison of the strength (when belt loads are not measured) and the performance of webbing materials with different loadelongation characteristics. A short (~3") cart stopping distance, from 25 mph, used in the European tests, produces increases in the magnitudes of both primary and secondary belt loading cycles over those obtained with a more "realistic" (~17") stopping distance, as encountered in actual automobile crashes".

Subsequent follow-up contracts at Calspan resulted in the creation of a general purpose 3 dimensional crash victim simulation program. The development resulted in the creation of the Crash Victim Simulator (CVS) [5]. In the 1980’s, the CVS was adapted for use by the Armstrong Aerospace Medical Research Laboratory at Wright Patterson Air Force Base and was re-named the Articulated Total Body (ATB). The principal investigator of the CVS/ATB development at Calspan was Dr. John Fleck. [6]. The pioneering work by Dr. Fleck included extremely efficient integration routines for economical execution of the program, dynamic memory sharing techniques which permitted the program to run with the limited amount of dynamic memory in computers during the era, and the addition of many extensions and refinements to extend and expand simulation capabilities.

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ighway Safety Research In 1952, a pioneer program in highway safety research, the Automobile Crash Injury Research Program (ACIR), was created by Cornell University with the objective of determining injury causation among occupants of cars involved in accidents, in order that the injuries might be prevented or mitigated through improved vehicle design. By the mid sixties, 31 states had participated in the program and provided over 50000 cases for study [7]. The main criterion for classifying severity in the ACIR program was through the use of comparison photographs of damaged vehicles.

In 1966 the National Traffic & Motor Vehicle Safety Act (P.L. 89-563, 80 Stat. 718) was passed which established the Federal Motor Vehicle Safety Standards (FMVSS) and the National Traffic Safety Agency (now known as NHTSA). The Motor Safety Act required regulators to establish federal motor vehicle safety standards to protect the public against "unreasonable risk of accidents occurring as a result of the design, construction or performance of motor vehicles" and also against "unreasonable risk of death or injury ... in the event accidents do occur."

At the time of signing the Safety Act into law President Johnson stated “Auto accidents are the biggest cause of death and injury among Americans under the age of 35”. In 1965, 50,000 people were killed on our nation’s highways. Since 1966, the Department of Transportation (DOT) has taken a compre-

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Figure 2: Highway Accident Fatality Rate from 1966 to 2005

hensive approach to reducing roadway fatalities by promoting strong traffic safety laws coupled with high-visibility enforcement and through rigorous vehicle safety programs and public awareness campaigns.

The success of the traffic safety program was demonstrated in year 2010 when NHTSA reported that the number and rate of traffic fatalities in 2010 fell to the lowest levels since 1949, despite a significant increase in the number of miles Americans drove during the year. Since 2005, fatalities have dropped 25 percent, from a total of 43,510 fatalities in 2005 to 32,788 in 2010. The fatality rate will be the lowest recorded since 1949, with 1.09 fatalities per 100 million vehicle miles traveled, down from the 1.13 fatality rate for 2009. The decrease in fatalities for 2010 occurred despite an estimated increase of nearly 21 billion miles in national vehicle miles traveled.

Before the introduction of the microprocessor in the early 1970s, computers were large multi-million dollar systems (like the IBM/360) which consumed entire floors of buildings, required their own cooling systems, and were owned by institutions like corporations, universities and government agencies. Computer users normally used punched cards to enter tasks into the computer and

individual computational ‘jobs’ on the computer were entered in ‘batch mode’ and controlled by Job Control Language (JCL). Output from the computers was generally printed output. These were used in conjunction with 9 track tapes (for storage), card punch and reader machines (for creating and reading program input) and terminals to provide to scientists, engineers and others number crunching capabilities unlike any utility ever before imagined.

The costs of operating large scientific mainframe computers were dropping significantly in the early sixties. A program which cost $100 to run in 1962 cost only approximately $5.65 in 1966 [8].

Other items which we take for granted today are processing speed and disk capacity. A measure of computation power is FLoating point Operations Per Seconds (FLOPS). In the mid 1960s FLOPS were at a rate of approximately 1 million, also known as a megaFLOP. In 2010, FLOPS were approaching petaFLOPS (1016).

Also disk and memory capacities were extremely limited on these computers. We have extraordinary processing capacity and power at our fingertips today with our notebook computers operating at petaFLOPS and containing gigabytes of memory and terabytes of disk capacities. The age of the notebook supercomputer is upon us now!

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Figure 3: HVOSM analytical representation of vehicle

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VOSM: Highway Vehicle Object Simulation Model Returning to the mid-60's the Calspan Corporation began development of a general mathematical model and computer simulation of the dynamic responses of automobiles under the direction of Ray McHenry [9].

The mathematical model, which was subsequently named the Highway Vehicle Object Simulation Model (HVOSM), included the general three-dimensional motions resulting from vehicle control inputs, traversals of terrain irregularities and collisions with certain types of roadside obstacles.

The development of the HVOSM included an extensive validation effort within which a series of repeated full-scale tests with instrumented vehicles was performed to permit an objective assessment of the degree of validity of the computer model [10].

The need for analytical capabilities in highway safety research becomes apparent when one considers the large number of variables that influence both the occurrence and the consequences of highway accidents. Actual accidents include an infinite variety of combinations of direction, speed, evasive maneuvers, obstacles, vehicle and terrain properties, vehicle occupancy and conditions of occupant restraint, Therefore to perform a rigorous evaluation of the benefits to be achieved by a given change in vehicle or roadside design one must include consideration of a representative sample of vehicles, operating conditions, occupancy and occupant restraints.

In a full-scale experimental evaluation, the generally poor repeatability (i.e. the scatter in results) makes it necessary to include several runs of each test condition. Obviously, a purely 24

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experimental evaluation procedure is both time consuming and expensive. Experiments also do not provide a capability of predicting responses of a complex, nonlinear system. Validated analytical procedures can serve to reduce the required number of full scale tests by providing a means of interpolating and extrapolating experimental results for widely spaced test conditions. They can also serve to provide a predictive capability and, thereby, a theoretical framework within which tests can be planned and experimental data interpreted. The highly nonlinear nature of the physical system, both in violent evasive maneuvers and in collisions, demands that realistic analytical procedures be programmed for computer solution.

At the time of the development of the HVOSM, an extensive body of literature existed on analytical studies of automobile dynamics, but the general approach at the time involved separate treatment of motions in the longitudinal plane (ride responses, performance and braking) and motions in the lateral plane (cornering behavior and stability). Furthermore, the equations of motion had generally been linearized. While such practices are acceptable in studies of small disturbance handling qualities, they are not appropriate for violent maneuvers at the upper limits of vehicle control. In view of the extended requirements for a realistic analysis of vehicle dynamics in near-accident and accident situations, where interactions between ride and cornering motions cannot be neglected, the nonlinear HVOSM computer simulation of automobile dynamics was developed to permit the study of simultaneous, large amplitude ride and cornering motions and to include an approximate treatment of collision forces.

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The HVOSM vehicle representation has fifteen degrees of freedom: 6 for the sprung-mass, and up to 9 for the unsprungmasses. Tire side forces are generated according to equations allowing for saturation to occur at large slip angles. The “friction circle” and the "friction ellipse" concepts are used to simulate the effects of braking and traction on the side forces. The simulated suspension forces include progressively stiffening, energy dissipating limit stops and a combination of coulomb and viscous damping. The sprung mass is represented as a rigid body with a peripheral layer of homogeneous, isotropic, deformable material. The assumed properties of the peripheral layer, with dynamic pressure directly proportional to depth of penetration, were based on the results of dynamic and static crush tests of automobile structures.

Some researchers in the field of highway safety have a tendency to view experiments, whether part or full scale, as being more real and believable than analyses. At least part of this tendency stems from the fact that physical experiments can be seen and photographed. Computer graphics displays can help in analysis by allowing the direct observation of computer "experiments", In actuality, many physical experiments are poorly defined and controlled. Instrumentation errors sometimes yield individual items of response that are not compatible with each other. For example, in the series of physical experiments that were performed to validate the HVOSM, a number of instrumentation difficulties were revealed by the comparisons with analytically predicted results. It is not intended to suggest that computer simulation can ever eliminate the need for physical experiments; Rather, the intention is merely to point out the fact that computer simulations can serve as valuable aids for interpreting the results of physical experiments with nonlinear systems, as well as for interpolation and extrapolation to other combinations of test conditions.

In 1969 the paper by Raymond R. McHenry on the HVOSM development entitled "An Analysis of the Dynamics of Automobiles During Simultaneous Cornering and Ride Motions", [11] was awarded the Crompton-Lanchester Medal from the Institution of Mechanical Engineers. Awarded by the Board of the Automobile Division for the best paper or for outstanding service considered to have special influence on the advancement of automobile engineering.

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he Astro-Spiral Jump In addition to the substantial effort in validation of the mathematical model, the HVOSM was also uniquely tested by designing an automobile stunt which was used both in a travelling auto-stunt thrill show and in the 1974 James Bond Movie, “Man with the Golden Gun” produced by United Artists Corporation [12].

As a part of the HVOSM development process, Calspan employed the services of professional stunt drivers in 1968 to perform maneuvers and stunts with an instrumented vehicle and, thereby, to generate vehicle response data in violent maneuvers for use in investigating the validity of the computer simulation. One of the included stunts was a fifty foot jump from a take-off to a receiving ramp. The degree of achieved correlation between analytical predictions and experimental measurements was found to be remarkably good in all of the included maneuvers and stunts. At the time, it was jokingly pointed out that Calspan had unintentionally developed a capability for the design and staging (i.e., via animated perspective displays on motion picture film) of auto thrill shows. A related, "far out" suggestion was the design of ramps to produce a combination of jump and rollover (i.e., a "spiral" jump), such that the stunt car would land on its wheels after passing over an obstacle in an inverted condition.

Subsequent to completion of development and validation of the HVOSM simulation in 1970, the thrill show ideas were given somewhat more serious consideration. Such an application would constitute both a challenging dynamics problem, similar in nature to a particularly violent single-vehicle accident, and an attention-getting demonstration of capabilities. It also had the appeal of a "fun" project to relieve a steady diet of crash protection studies.

In November of 1970 Ray McHenry contacted Jay Milligan, Jr., President, J.M. Productions Inc., of Hamburg, New York, regarding his possible interest in the design of a new auto thrill show stunt and/or the establishment of speed and dimensional tolerances for existing stunts.

The HVOSM simulation does not, of course, provide direct guidance for invention. Its application is equivalent to performing experiments with a fully instrumented-vehicle. Therefore, the analytical study of the spiral jump stunt concept consisted essentially of a trial and error process of exploratory changes in ramp configurations. The initial simulation study indicated that the combined needs to run both ends of the automobile over the same ramp profile in sequence and to generate a large roll acceleration in the 40 MPH speed range would create a serious problem in achieving acceptable pitch and yaw behavior.

The limitation to the speed range of 40 MPH, which is based on space restrictions that generally exist for thrill show performances, produced a corresponding limitation on the time in the air that was available for the 360 degree roll-over. Thus, a large roll velocity (approximately 230 degrees per second) had to be generated to achieve a "wheels down" landing on the receiving ramp. The sequential traversal of the take-off ramp by the front and the rear wheels, when combined with the nonlinear suspension characteristics during the traversal (i.e. front suspension "bottomed out" throughout the roll impulse) was found to create a response sequence in which the rear wheels

Figure 4: The first live performance of the astro spiral jump in Houston, TX 1972

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Figure 5: Comparison of test driver ramp to ramp jump and HVOSM simulation predictions

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Figure 6: Spiral Jump driver’s view to takeoff and landing ramps

cleared or only lightly touched the "roll-impulse" end of the ramp.

As a result of this sequence, the initially predicted responses retained a "nose-up" attitude during the entire jump and were found to include excessive yawing. Attempts to achieve a corrective pitch impulse at either of the rear wheels were unsuccessful, The rear wheel that was moving up fastest cleared any ramp configuration that the "bottomed out" front suspension had traversed, An impulse sufficient for the desired pitch response, when applied at the other rear wheel, acted to excessively reduce the roll velocity. Therefore, it became necessary to consider minor vehicle modifications to achieve the desired combination of linear and angular velocities at the end of the take off ramp. The necessary vehicle modification consisted of an auxiliary contact point on the rear axle, for which the primary loading occurred on the last ten feet of the take-off ramp. The additional contact on the rear axle was also found to require a relatively low side-force capability to avoid unwanted yaw accelerations.

In the 60’s and 70’s Ray worked with Bill Milliken[13] at Calspan. Ray has always said that without Bill’s perseverance and influence the spiral jump project would have never been completed.

Bill fought for the project and fought off the Calspan management who were paranoid about liability. Bill was somehow able to arrange to have the original AMC Javelin vehicle measured at the GM Proving Grounds in Michigan. Yes, that is correct; somehow Bill was able to arrange to have an AMC vehicle measured at the GM facility. Talk about pull! Ray, my brother Stan McHenry and Doug Milliken (Bill’s son) all drove from Buffalo to Michigan and on to the GM proving grounds with the AMC Javelin to have the measurements done!

The first live performance of the “spiral jump” stunt was performed at the Houston Astrodome in 1972 before a sellout crowd of more than 100,000. For the actual ‘traveling stunt’ the target speeds, weight and distance were 40 +/- 1 MPH and 1461 +/- 3 kg, and 13.85 +/- 0.03 m. A thrill show toured with the stunt both before and after James Bond picked it up for the movie. For many of the tour shows in the US, the drivers came in slow (below the low speed) and damaged the suspension and landing ramp on landing.

Bumps Willard, who performed the stunt flawlessly (one take!) for the Bond movie also toured Europe with the thrill show and hit the jump perfectly every time!

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In 1976, after 10 years of development, refinement and applications of the HVOSM by Calspan as well as other research organizations, under FHWA contract Calspan documented all the various developments, refinements and validations of the HVOSM [14].

Since 1976 Ray and I have performed a number research projects which included further refinements and enhancements of the HVOSM under subcontracts with Jack Leisch and Associates [15], Midwest Research Institute [16], Calspan [17] and the Highway Safety Research Center of the University of North Carolina [18] as well as through internal research[19].

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MAC – Simulation Model of Automobile Collisions Around 1970 the SMAC computer program was created by Ray and his team at Calspan on year-end funds.

Year-end funds are left over research money which needs to be used before the end of the year (‘use it or lose it’).

Ray was interested in demonstrating the feasibility of a mathematical model of automobile collisions which could achieve improved uniformity and accuracy in the interpretation of evidence in automobile accidents.

Prior to the creation of SMAC, the general practice in the reconstruction of automobile collisions was to consider the collision and the trajectory phases of the event separately. This division of the analytical task was based on two assumptions: (1) that the effects of tire forces are negligible during the existence of collision forces and (2) that the collision event can be assumed to occur instantaneously.

While these assumptions appear to be reasonable, their application had been found in some impact configurations to produce significant errors during the collision. For example, in moderate-speed intersection collisions multiple contacts frequently occur – front-side followed by side-to-side and or rearto-side contact, normally referred to as a “side-slap” secondary contact [20]. If a secondary contact is neglected in a collision reconstruction major errors can be produced in predictions of spin-out trajectories. Also, if tire forces are neglected throughout the time during which the collision contacts occur, significant errors can be introduced during the lateral motions of the vehicle between impacts. Therefore the SMAC program was created with provisions that both the collision and tire forces be considered simultaneously.

SMAC is an "open-form" accident reconstruction program. A requirement of "open-form" programs like SMAC is that the user must initially estimate the impact speeds.

One of the difficulties which arose in setting up SMAC simulations by the NHTSA investigative teams was that the program requirement of an initial estimate of the impact speeds which was not always an easy task. Also, the user had to provide vehicle properties and specifications, many of which were not readily available. Those requirements, combined with the relatively high cost per run for a SMAC simulation run, required that a pre-processor be created which could provide the initial estimate of the impact speeds.

The CRASH computer program [21] was created to assist SMAC users in determining a first estimate of impact speeds.

So let us digress for a moment to discuss CRASH:

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RASH - Computerized Reconstruction of Accident Speeds on the Highway The original CRASH program utilized both piecewiselinear trajectory solution procedures and a damage analysis procedure to provide an initial estimate of impact speeds. The CRASH program was subsequently adopted by NHTSA as an integral part of the NASS investigations.

The National Accident Sampling System (NASS) was established in 1979 as part of a nationwide effort to reduce motor vehicle crashes, injuries and deaths on the US highways. The NASS General Estimate System (GES) collects data for nonfatal crashes, and combines that data with information on fatal crashes from the Fatal Analysis Reporting System (FARS).

Data for GES comes from a nationally representative sample of police reported motor vehicle crashes of all types, from minor to fatal.

The system was created to identify traffic safety problem areas, provide a basis for regulatory and consumer initiatives, and form the basis for cost and benefit analyses of traffic safety initiatives. The information is used to estimate how many motor vehicle crashes of different kinds take place, and what happens when they occur.

GES data are used in traffic safety analyses by NHTSA as well as other DOT agencies. GES data are also used to answer motor vehicle safety questions from Congress, lawyers, doctors, students, researchers, and the general public.

A requirement of "openform" programs like SMAC is that the user must initially estimate the impact speeds.

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The rationale for the use of the CRASH program was that for statistical studies, the average error in severity determinations is more important than specific individual errors. The CRASH program, with it's question and answer mode, vehicle categorization, single step solution procedure, and most importantly low cost, redirected the NHTSA interest from SMAC towards the CRASH computer program.

The original form of the CRASH computer program, which culminated in the CRASH3 version, was not intended to be a detailed, highly accurate reconstruction program. Rather, it was developed to serve as a simple preprocessor for the SMAC program. While the results of CRASH3 applications can be useful in providing approximate measures of accident severity for use in statistical studies, where the average error is most important, it has been demonstrated in validation tests to produce results which when compared to those of full-scale crash tests can include individual errors as great as ±45%[22].

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“”

Obviously any CRASH results utilized in individual case reconstructions, like for police and/or litigation purposes, need to be further tested and refined with more sophisticated accident reconstruction techniques.

The first project I worked on in the field of Highway safety was in 1979 and was related to a refinement of CRASH3 under contract with NHTSA [23]. My part of the contract was evaluating the results of a large number of SMAC simulations of various accident types to be used to refine SPIN2 of the CRASH3 trajectory solutions procedure.

To improve the accuracy of approximations of separation velocities, provisions for the introduction of a residual linear velocity at the end of the rotational motion and the development of empirical coefficients, in the form of polynomial functions of the ratio of linear to angular velocity at separation, were incorporated in the SPIN2 analytical relationships of the CRASH program. Since the separation velocity ratio is initially unknown, a solution procedure was developed whereby several trial values of the ratio, based on an approximate equation, were used to test multiple solutions.

and moments acting on the vehicles if the movement during the collision is ignored[24]. (Note that until the 2000’s personal computers were too slow to consider a SMAC collision iteration scheme, however a SMAC trajectory iteration scheme incorporated into the CRASH solution procedure was investigated in the late 1990s [24])

We also worked on refinement of the CRASH damage analysis procedure to incorporate restitution

For the refinement of the SPIN2 coefficients, a representative sample of actual accident cases was selected from the NCSS files for use in the study and then reconstructed with the SMAC computer program. For each of the SMAC reconstructions, separation information was used to formulate a basis for a refinement of the SPIN2 empirical coefficients.

A careful examination of the time-history plots of linear and angular velocities for all of the cases in the sample revealed a significant number of cases in which the SMAC-predicted behavior deviated from the analytical assumptions upon which the SPIN2 routine is based. Attempts were undertaken within the research project to discriminate characteristics of separation conditions. Unfortunately, only partial success was achieved in the attempts to accommodate deviations by means of the use of logic and discriminators. As a result, a realistic appraisal of residual scatter in the empirical fits led to the conclusion: "To achieve a general improvement in the reliability and accuracy of approximations of the angular and linear velocities at separation, a step-by-step time history form of trajectory solution should be implemented."

Since working together on that project, Ray and I have researched and published numerous papers to further refine the CRASH3 solution procedures.. The objective in our refinements of the CRASH3 accident reconstruction procedures has been to simplify the input requirements of the program while providing a significantly improved correlation of the reconstruction results with known test results. A secondary consideration in the form of the refinement has been to limit the total computational time for convergence on a solution to a reasonable amount of time.

With respect to refinement of the CRASH3 trajectory solution procedure, we have investigated the inclusion of provisions for activating the angular momentum solution. These refinements required provisions for approximating changes in positions and orientations during the contact phase of collisions to avoid significant changes in the directions and magnitudes of forces

We also worked on refinement of the CRASH damage analysis procedure to incorporate restitution [25]. Crush coefficients for vehicle collision analysis are predominantly based on impact speeds and damage measurements from rigid, fixed barrier crash tests. The residual damage is correlated with the impact speed by means of fitted linear relationships. In general, there is no consideration given to the effects of restitution in applications of the fitted crush coefficients. However, the ignored effects of restitution on the total impact speed change, corresponding to a given amount of residual crush, are compounded by the fact that restitution acts to reduce the amount of residual deformation, for a given maximum dynamic crush, while also acting to increase the total impact speed change. Thus, substantially different vehicles can share nearly equal slopes and intercepts in CRASH-type plots of the approach period speed-change as a function of residual crush. This can occur even though the actual exposure severity for a given residual crush may be significantly different.

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alidation of Computer Models One of the problems associated with the development and refinement of any accident reconstruction techniques and of research is that of demonstrating correlation with full-scale tests. A test matrix of 18 full-scale crash tests were performed in 1978-1980 which became known as the Research Input for Computer Simulation of Automobile Collisions (RICSAC) crash tests [26].

For each of the RICSAC tests, a minimum of 13 accelerometers were mounted on-board each vehicle to record acceleration components at six to seven stations. At three locations triaxial (XYZ) packages were installed ("hard mounted") to provide coverage between the front and rear of the vehicle. The front steer angles were measured on each vehicle by a linear stroke potentiometer attached to the vehicle steering linkage.

The time history of the change in vehicle yaw, pitch and roll angles and yaw rate were recorded by two-degree-of-freedom, free gyroscopes and a rate gyro.

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The RICSAC tests were specifically designed to serve as standards for such comparisons and were successfully used for comparison validation purposes the CRASH and SMAC computer programs.

Unfortunately, in some studies which included evaluating the correlation of computer codes with RICSAC there have been various levels of interpretation and acceptance of the measured results. Questions have been raised as to the validity of some of the reported RICSAC test results.

Since there had been no consensus on the interpretation of some of the results of the RICSAC tests, Ray and I performed an intensive independent effort toward achieving proper and generally acceptable interpretations of the RICSAC test data [27]. The conclusions of that research were that (1) the RICSAC data are accurate and are suitable for their intended purpose of testing the validity of reconstruction techniques, (2) previously reported findings of gross errors and violations of Newton’s laws in the reported RICSAC data are erroneous and (3) the SMAC program once again demonstrated excellent correlation with properly analyzed full-scale test results

S

MAC – The Simulation Model of Automobile Collisions (continued) The SMAC program was initially developed in the 1970's when all development of computer code was performed on time-share mainframe computer systems which had limitations on the amount of available memory and processing time and for which the costs to perform a single SMAC simulation were relatively high . (e.g., circa 1971, "The range of costs…has been approximately $25.00 per application run" for the SMAC program). These limitations during the original development of the SMAC program guided the selection of many of the simplifying assumptions of the mathematical model.

Since the early 80's and particularly by the mid to late 1990’s, the prevalence of powerful computers creates an availability of virtually unlimited and inexpensive computer resources. This has inspired a detailed re evaluation and refinement of computer codes, particularly those developed in the 1970's.

In light of the advances in computer technology and our continuing research, development and refinement of the SMAC model, we presented and implemented refinements in the definition of the collision interface, the definition of collision type, the vehicle proximity and collision detection logic, and the form of supplementary impulsive constraints on relative motions [28,29].

Since the initial development of the SMAC program, there has also existed a need to simplify the application process. The ultimate simplification would entail an automatic iteration procedure.

The working hypothesis of the presently described research on the automatic iteration of SMAC, as well as that of other simulation-type analytical approaches to accident reconstruction, is that a unique set of impact conditions is required to achieve an acceptable match of all of the documented evidence (both damage and trajectory). The use of quantitative measures of the overall "fit" to the documented evidence and applications to experimental crash tests provide a means of testing the hypothesis, as well as demonstrating reconstruction accuracy and convergence rates.

As any SMAC user is aware, many iterations of the program may be required to go from an initial approximation to an acceptable match of the measured trajectory and damage targets. Throughout the iterative process, the impact speeds and speed change results may not change significantly. Also, what constitutes an acceptable match can vary widely among users.

Sometimes the focus is on a detailed match of the positions of rest; sometimes the focus is on a match of damage locations and extents on the vehicles. There is currently no standardized measure of the correlation of SMAC results with the accident evidence. Since the initial development of the SMAC program, there has existed a need to simplify the application process.

In 2003, we created an automatic iteration procedure for the SMAC computer program [30] which proved the working hypothesis. The use of quantitative measures of the overall "fit" to the documented evidence and applications to experimental crash tests provided a means of testing the hypothesis, as well as demonstrating reconstruction accuracy and convergence rates.

The reported results demonstrate that the SMACITER program successfully converges toward evidence matches in a variety of impact configurations. In initial applications wherein SMAC generated "evidence' was used the errors in impact speeds generally run less than approximately ± 2%. With measured evidence from full-scale tests, wherein the deviations from a perfect evidence match run larger, the errors in impact speeds have been found to run less than approximately ±10%.

S

MAC3D Combining SMAC and HVOSM into one program In 1998, I was hired by CBS News to reconstruct the Princess Di accident for the television program “48 Hours”. At that same time we had been working on a 3D collision simulation program which combined the collision capabilities of SMAC with the 3 dimensional vehicle dynamics simulation capabilities of HVOSM. We were provided the survey information for the tunnel, the vehicle information and we used the program, SMAC3D, to simulate the vehicle traveling into the Pont de l'Alma road tunnel in Paris, France, and striking the support post (In that tunnel they do not have guardrails in front of the support posts). The results were presented and I answered questions in interviews broadcast on June 11, 1998 and August 31, 1998. The eighteen-month French judicial in-

Figure 7: Still photos from simulation animation of the princess Di Accident reconstruction

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“”

vestigation which concluded in 1999 correlated closely with the speeds and findings of my investigation and with the simulated reconstruction with the prototype SMAC3D.

There are also many high end graphics and animation programs available which can be used to create high-end animations of the results of accident simulations and reconstructions.

Until the early 2000's, the limitations in processing speed of personal computers limited our continued development of the SMAC3D model to simple internal research. Since 2000, we have been testing and refining a 3D simulation and reconstruction tool which merges the strengths of SMAC and HVOSM into a single program.

T

he Future The process of reconstructing a motor vehicle collision involves collecting all available information about the interaction of the vehicles including vehicle trajectory information, damage information, vehicle specifications and scene information.

The trajectory information is gathered based upon the police measurements, photographs and scene evidence documentation (skid marks, gouges, etc.). To characterize the interaction of the vehicles, the approximate location of the area of impact, the measured positions of rest and any skid and gouge marks should be memorialized. Technological advances in survey and measurement equipment have made equipment available to police and investigators which can quickly, efficiently and accurately memorialize vehicle accident scenes.

The damage information includes measured dimensions of the damage locations and extents. The standard procedure by which damage is characterized is the Collision Deformation Classification (CDC, [31]) and the Equidistant Crush Measurement (ECM, [32]).

Collecting vehicle specifications and scene information (roadway layout and topography) completes the required data to permit the performance of an accident reconstruction.

In 2010 we were approached by Mike Kennedy about consulting with him on his new venture, ARAS360. With ARAS360 Mike has envisioned and is creating an all encompassing accident reconstruction tool to be used by collision analysts.

ARAS360 takes the collision analyst from the initial collection of evidence to the final reconstruction analysis with all steps in between in a seamless and enjoyable user experience.

There are many CAD and survey software programs available which can be used to collect and display information on scene and vehicle accident data. Many other program vendors have created commercial versions of accident reconstruction tools

and programs, including versions of SMAC and HVOSM. There are also many high end graphics and animation programs available which can be used to create high-end animations of the results of accident simulations and reconstructions.

In summary, after working in the field for over a collective 80+ years, and having been a witness and participant in the phenomenal and astounding breakthroughs in computational power and accessibility, particularly with respect to the field of highway safety, we see our work as a consultant to ARAS360 implementing a 3-dimensional collision and simulation model as an opportunity for another quantum leap into the future in the highway safety field. Our hope is that someday in the near future police and investigator applications of ARAS360 will generate a large volume of high quality accident reconstruction data, including injury/exposure definitions, that can then be used by NHTSA/NASS and other governmental agencies or researchers to serve to further guide improvements in highway safety.

Figure 8: Preliminary Comparison of a frame from film of ARC-CSI test and a frame from a Collide3D simulation of the collision.

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R

eferences 1 Consumer Reports, October 1961, Articles by Michelson and Tourin

17 Rollover Potential of Vehicles on Embankments, Sideslopes and Other Roadside Features, Deleys, Parada, DTFH6183-C-0060, August 1986., Also: SAE paper 870234

2 "Consumer Union's Dynamic Tests of Seat Belts", Michelson, Torin, 5th Stapp Automotive Crash and Field Demonstration Conference, September 1961

18 Safe Geometric Design for Mini Cars, Council, Reinfurt, Knoblaunch, Stewart & McHenry, DTFH61-84-C-067, November 1986. Also SAE paper 870233

3 "Dynamic Tests of Automobile Passenger Restraining Devices", Michelson, I., Aldman, B., Tourin, B. and Mitchel, J. Presentation to Committee No. 6, Department of Traffic and Operations, Annual Meeting of the Highway Research Board, Washington DC, January 7, 1963

19 "Simulation Models of Vehicle Dynamics", B.G. McHenry, April 1992, Transportation Research Board Circular "Beyond the Green Book".

4 “Analysis of the Dynamics of Automobile Passenger-Restraint Systems”, McHenry ,7th Stapp Car Conference Proceedings, SAE, 1966 5 “Development and Validation of a Computer Simulation of a Crash Victim in Three Dimensions”, Bartz, SAE Paper 720961, SAE, 1972 6 “Improvements in the ATB/CVS Body Dynamics Model”, Fleck, 13th International Technical Conference on Experimental Safety Vehicles, S8-W-20, 1991 7 “A Review of ACIR Findings”, Campbell, B.J., 8th Stapp Car Conference, 1966 8 “Evolving Computer performance 1963-1967”, Kinght, K.E.,DATAMATION, pp 31-35 January 1968 9 Contract CPR-11-3988 with the Bureau of Public Roads (now known as the Federal Highway Administration (FHWA) 10 "Vehicle Dynamics in Single Vehicle Accidents-Validation and Extensions of a Computer Simulation", McHenry, R.R. and Deleys, N.J.,,Calspan Report No. VJ-2251-V-3, December 1968.(PB 182 663) 11 “An Analysis of the Dynamics of Automobiles During Simultaneous Cornering and Ride Motions”, Raymond R. McHenry, Symposium on Handling of Vehicles Under Emergency Conditions, Institution of Mechanical Engineers (London), Loughborough University of Technology, 8 January 1969 12 “The Asto Spiral Jump – An Automobile Stunt Designed via Computer Simulation”, McHenry, R.R., ,SAE paper 760339 13 See Equations of Motion: Adventure, Risk and Innovation ,the autobiography of William F Milliken for many more amazing stories of his (so far) 100 years of accomplishments!

Also see the article Mister Supernatural, by Karl Ludvigsen, Automobile Quarterly, First Quarter, 2004

20 “Development of a Computer Program to Aid the Investigation of Highway Accidents”, McHenry, R.R.,,Contract FH11-7526, NTIS PB 208537, Calspan Report VJ-2979-V-1, December 1971 21 “The CRASH Program – A Simplified Collision Reconstruction Program”, McHenry, R.R., ,Proceedings of the Motor Vehicle Collision Investigation Symposium, Calspan, 1975 22 “CRASH3 Technical Manual”, Tsongos, N.G., ,U.S. DOT, NHTSA, NCSS, Accident Investigation Division, July 1986 23 "National Crash Severity Study - Quality Control, Task V: Analysis to Refine Spinout Aspects of CRASH", McHenry, R.R., McHenry, B.G., Calspan Field Services, Inc. ZP6003-V-4; DOT-HS-6-01442, January 1981 24 "CRASH-97 - Refinement of the Trajectory Solution Procedure", McHenry & McHenry, SAE Technical Paper No. 970949 25 "Effects of Restitution in the Application of Crush Coefficients", McHenry & McHenry, SAE Technical Paper No. 970960, also in Crash Reconstruction Research: 20 Years of Progress (1988-2007), published by SAE March 20008, product code PT-138 26 "Research Input for Computer Simulation of Automobile Collisions", McHenry, R. R., Lynch, J. P., Segal, D. J, ,Calspan Report ZQ-6057-V-1, Contract DOT-HS-7-01511, Jun 1977, 27 "RICSAC-97 - A Reevaluation of the Reference Set of Full Scale Crash Tests", McHenry, B.G., McHenry, R.R, SAE paper 97-0961 28 "SMAC-87", McHenry & McHenry, SAE Technical Paper No. 880227, International Congress and Exposition, Detroit, Michigan 29 "SMAC-97 - Refinement of the Collision Algorithm", McHenry & McHenry, SAE Technical Paper No. 970947

14 "Highway-Vehicle Object Simulation Model - 1976", Segal, D, "Vol I - User's Manual", (PB-267401) ,"Vol II - Programmer's Manual" (PB-267402) ,"Vol III - Engineering Manual - Analysis" (PB-267403) , "Vol IV - Engineering Manual -Validation" (PB-267404)

30 “SMAC2003: The Automatic Iteration of SMAC”, McHenry, B.G., McHenry R.R, SAE paper 2003-01-0486

15 “Safety and Operational Considerations for Design of Rural Highway Curves, Glennon, Neuman and Leisch,Contract No. DOT-FH-11-9575, PB-86139 664/AS, December,,1985.

32 SAE Standard J2433, Equidistant Crush Measurement Techniques, SAE Standards for Works In Progress

31 SAE Standard J224A, Collision Deformation Classification, 2011-05-18

16 Work Zone Design Considerations for Truck Operations and Pavement/Shoulder Drop-Offs, Glennon, Graham, ,Contract No. DTFH61-80-CO0146, Feb. 1984.

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the lly at a u n n a e Offered nferenc o C h s a Cr ARC-CSI csi.com www.arc

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E

ach year, the ARC-CSI Crash Conference draws an international audience to Las Vegas in search of the latest information concerning crash reconstruction. In addition to speakers that are prominent in the field of collision analysis, the conference traditionally showcases an entire day of full-scale, instrumented crash tests. These tests are typically conducted by top independent researchers in the field with support from local law enforcement and major vehicle manufacturers. For the 10th anniversary of the conference, the ARC-CSI organizers made available an opportunity for a limited number of attendees to work “behind the scenes,” learning what goes on in the preparation and execution of successful vehicle crash testing through what was called the inaugural “ARC-CSI Crash Team Boot Camp.”

Most people when they hear the words “boot camp” conjure up images of a military drill instructor barking commands in the face of some young recruit with a terrified look on his face.

This is followed by mental images of intense physical activities and mental stress all in an unfamiliar setting. While the military drill instructor was replaced by Sergeant-At-Arms, Rusty Haight, and the terrified looks were replaced by smiles, those who participated in the inaugural ARC-CSI Crash Team Boot Camp will attest to the intense physical activities and mental stress that accompanied our “boot camp” experience.

they had gotten themselves into and wondered if the benefit was going to justify the cost (expensive, but well worth it, read on). While the boot camp experience is not for the passive or casual member, the long hours, hard work, and active participation met participants’ high expectations and quickly erased any doubts about the benefits of the experience. The experience has delivered what we believe will be long term friendships and given us one valuable tool for our collision analysis toolbox.

While it is difficult to paint a picture of our experience with words, we have tried to give future participants an idea of what they are getting themselves into and what they can expect to get out of the experience.

C

rash Team Boot Camp – Day One Showing up at an early Saturday meeting before Monday’s Crash Testing, a dozen individuals met for the first time. What was striking about this small group was that they represented the demographics of the overall Conference with attendees from the fields of Law Enforcement, Engineering, Biomechanics and Human Factors. Experience levels ranged from a little to a lot.

The morning was filled with instruction from a number of the Crash Test Crew organizers, including Rusty Haight on running the actual tests on the track; Bob Anderson on the instrumentation available to be fitted in each vehicle; Sean Haight

Before attending the ARC-CSI Crash Team Boot Camp, most of the participants had high expectations and were looking forward to an opportunity to work side-by-side with experienced people in the field of crash testing. Others were not sure what

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Collision Magazine 35

on recording the tests with video; and Kent Boots on documenting the test sites and vehicle profiles using total station technology. A rather mysterious Mr. Rosenfeld was also present, working with his latest remote-steered vehicle device – the “Phantom Driver.”

With instructions in hand, the morning ended with the Boot Camp participants inspecting the two test vehicles that would be made available to them. While we had not started our crash test preparations the experienced Crash Test Crew was already hard at work prepping all of their vehicles for Monday. This was our first real clue to the amount of preparation it takes to conduct a successful crash test.

After a quick lunch, the Boot Camp participants met to hammer out a consensus (try that with a dozen strangers, many of whom are established experts in their field) on general test configuration and the equipment and dummy requirements for each of our test vehicles. It was quite a challenge to try and meet every one of the team members’ wants and needs in testing, data acquisition, analysis of the data and presenting the results to the ARC-CSI Crash Conference attendees.

After some initial struggles, a team leader was elected and a course was set to meet our expectations as well as those of the Boot Camp organizers. One thing that made this go smoothly was each member listed their individual strengths as well as an area of the crash testing process about which they would like to learn more. This made dividing up the various responsibilities much smoother. With plan in hand, we retired for a good night’s sleep (for many, their last before we presented our findings the following Thursday).

D

ay Two Day two started for the Boot Camp crew with an 8 am trip to the crash test facility located about 15 miles north of the city at the Las Vegas Motor Speedway. We were met with excellent weather and a bit of an air show by the fighter jets from nearby Nellis AFB. After applying liberal amounts of sun screen, the Boot Camp crew set about implementing their plan by preparing their vehicles for Monday’s crash testing. Tools were borrowed, advice was given, and once we got use to the idea of ripping up carpets and drilling holes through roofs, floors and doors, our work was completed quickly; but then we only had to prep two vehicles for our crash test. While we worked to complete our preparations, the established Crash Test Crew was hard at work prepping more than 12 other vehicles for the remainder of the scheduled crash tests. Our preparation for day two ended with us practicing our test vehicle timing to make sure our two vehicles would

arrive at the same place at the same time in the planned impact configuration on Monday in front of the Conference attendees.

Once we were confident we were prepared for Monday, most of the Boot Camp crew pitched in to work on the rest of the dozen or so test vehicles with some staying past sunset. Since most of the test vehicles were to be fitted with the same sets of instrumentation costing tens of thousands of dollars, and with the need to remove the equipment overnight for security reasons, the installation of mounting hardware was done to each vehicle to speed up test day preparations. By the end of day two, we had all had a chance to experience the intense, detailed preparation that goes into planning for a single crash test, much less the seven or eight in a row that the main Crash Test Team were planning to deliver.

T

est Day If we thought day two at the test track started early, test day beat it by a couple of hours (6 am start!), as the Boot Camp crew arrived just after sunrise, along with the rest of the Crash Test Crew. Our test would be the second of the morning, so we hustled to get all the test equipment back on board, all the cameras aimed and the speed timers timing. We really did not have time for one more dress rehearsal, but everyone felt confident from Sunday’s consistent timed runs. Once the instrumentation was onboard, our child seat and dummies in place, and our live (for now) test driver behind the wheel, we were ready to go. And go we did – the test setup was robust enough to survive one false start, and the test driver (Rusty Haight) was experienced enough to hit the second run right on the money.

With our test day pressures over early, the Boot Camp Crew made the most of the opportunity by getting heavily involved with the rest of the day’s testing. While being in the grandstands and viewing the aftermath of each test is instructive, being a part of each vehicle’s preparation and instrumentation download is definitely an extremely worthwhile addition to the experience. Again, some of the Boot Camp Crew stayed well into the evening to help get all of the vehicles and scenes documented and the equipment put away. Test day ended with a tired Boot Camp Crew, but it was a “good tired,” to be sure.

P

resentation Preparation If we thought that the bulk of the work was completed after the crash test ended, we were very wrong. We collected several gigabytes of data including accelerometer data, hundreds of photos, multiple videos, crash (CDR) data and various other sensor data from our crash. Trying to shift through and process all of the data was a daunting task that we did not begin immediately after the crash – and we should have. Both Tuesday and Wednesday night, many members of the team were crunching numbers and preparing slides well past midnight. All this was done to have our presentation prepared in time to get it on the Conference participant DVD. We probably spent an average of 40 – 45 hours per team member (or more) not including Saturdays classroom session working on only one crash!

P

resentation Day Fast forward from a tired Monday night to a nervous Thursday morning: Somewhere between attending the regular Crash Conference presentations; the Boot Camp Crew’s analytical minds went to work on the data recorded from our two test vehicles. The appropriate charts and graphs were prepared, and the conclusions that came from the data were formulated. All of the test data was submitted in usable form to Conference organizers on the night before the 36

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crash test presentations for inclusion in the Conference DVD. With helpful critique from biomechanics engineer Dr. Judson Welcher, the Boot Camp Crew finalized a PowerPoint presentation of our test experience for the Conference’s last day. With presentation assignments made, a crowded podium of team members presented a small portion of our Crash Team Boot Camp experience.

W

as It Worth It? This experience was a great way for the Boot Camp members to learn “hands-on” the necessary skills and equipment required for crash testing. Learning from highly skilled individuals who have already made most of the mistakes was invaluable. Learning about the equipment and instrumentation the ARC-CSI Crew uses and its abilities and limitations was an invaluable asset from this experience.

The member of the Boot Camp Crash Team would overwhelmingly recommend this experience to anyone who has an indepth interest related to crash testing, is willing to work hard, and has a hands-on attitude.

What did we learn? We learned what goes in to planning, executing and presenting a crash test – much more effort than you would believe or understand without this experience. We learned that while there may seem to be down time as a spectator, when you are on the track, down time does not exist.

Between getting vehicles into position, getting them instrumented, crashing them, collecting data, removing instruments, and then repeating the procedure seven or eight times in one day, there is no down time. That doesn’t even begin to address dealing with all of the mechanical issues that old cars always have! In order to crash them, you have to get them to run and drive first. Lastly, we learned that you will get out of this experience what you put into it. If you choose to stay on the sidelines and do the minimum or nothing just to be able to put this on your resume, you are wasting your time and the team’s time. If you choose to get fully involved and pitch in wherever needed, including weighing cars, pushing cars around, drilling holes or whatever else is necessary, you’ll have a great experience and learn more than you can imagine. You gain a new respect or appreciation for team members from outside your area of expertise (for instance, on our team, some engineers gained a new appreciation and respect for law enforcement and

some law enforcement officer developed a new attitude about engineers!). If you are lucky, you will also make some friends and great contacts along the way!

Much like the military recruit’s feeling of accomplishment on graduation day, the members of the inaugural Crash Team Boot Camp left the experience with a sense of accomplishment and lessons learned that will last a life time.

So, were the hours long, the work a bit dirty?

YES!

Did we each learn something from related fields that we hadn’t worked on before? YES! Did we enjoy each other’s company and solving problems on the fly? YES! But overall was it worth it? Well, was it recruit?

“Sir, yes sir!!!”

Inaugural Crash Team Boot Camp Participants:

www.collisionpublishing.com

Adam

Crepin

Semke Forensic

Nigel

McDonald

Collision and Safety

Joseph

Yates

Otto Laboratories

Stephen

Plourd

SLPI Inc

Joseph

Awad

Forensic Injury Consulting

Terence

Fischer

Fischer Forensic Services

Grant

Johnston

Grant Johnston Consulting Engineers

Susan

Bowley

Bowley Consulting LLC

Mathew Martonovich Ogden Engineering & Consulting David

Hallman

Crane Engineering

Rob

Madden

Colorado State Patrol

William

Redfairn

Las Vegas Metro PD

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t s w e e T i v h e s R a Cr a t a d

m a e T mp h a s C a r C oot B

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his year’s Boot Camp team gave twelve people the chance to plan and execute a full scale, instrumented crash test. Camp started on Saturday, with instructional input from an expert crash team. Instructors included Rusty Haight on how he’s put together in excess of 950 crashes, Bob Anderson on his instrumenting of crash test vehicles, Sean Haight on the various photo and video equipment necessary to capture all of the details, and Kent Boots on documenting the vehicles and scenes. With support from experts in multiple fields and instruction on the use of state-of-the-art instrumentation, the team was ready to go. Also available to the team was the mostly willing participation of Rusty Haight as the bullet car driver.

Once the Boot Camp crew learned that there were two vehicles along with a live driver to use in the test, the team went to work deciding on a test configuration. A Ford Crown Victoria, the workhorse of the crash test fleet, to be driven by Rusty was decided on as the bullet vehicle. The Ford was equipped with frontal air bags, seatbelt pre-tensioners, and downloadable air bag (ACM) and powertrain (PCM)

control modules. A Hyundai Sonata sedan was provided to be used as the target vehicle. The Hyundai was equipped with frontal air bags as well as front-seat-mounted side air bags, though its air bag control module could not be downloaded using the Bosch CDR system. Also made available to the team were two non-anthropomorphic test dummies; a male adult (approximately 50 pounds) and an infant in a car seat with tether attachment.

Track setup began with an agreed upon maximum delta-V for the Crown Victoria driver of 20 mph. For the Boot Camp test, a common accident configuration was chosen – a slow left-turning or U-turning car entering the path of an opposite direction, higher speed vehicle. This gave an angled impact, with the right side of the turning target vehicle being struck by the front of the bullet vehicle. The estimated approximate angle of impact to get the Hyundai’s front and side air bags to fire was approximately 45 degrees, and the Hyundai approach speed target was 8-10 mph. The angle of impact was selected in an attempt to deploy both the front and side air bags of the target vehicle. The angle was also selected to get the principal directions of force close enough to the vehicles’ centers of mass where there would not be a great deal of yawing post-impact.

The infant and car seat was placed in the right rear of the Ford,

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and the adult male dummy was seat-belted into the right front passenger seat of the Hyundai.

Vehicle weights were measured and momentum calculations were done that yielded a maximum approach speed for the Crown Victoria of 38 mph. When attempting a “MovingMoving” test, the timing to get the vehicles to hit as planned is critical. In this test, the preliminary timing was based on time/ speed/distance calculations, but it was necessary to practice the timing using a push car to shove the Hyundai out into the Crown Victoria’s path at just the right moment and at just the right speed.

T

est Results Table 1 below shows the measured results from the crash test.

V

ehicle instrumentation set-up Both test vehicles were equipped with a Video VBOX Lite which recorded the GPS position and speed of the vehicles at 10 hertz, using the Doppler Effect. The Video VBOX Lite has a high resolution camera and a low resolution camera available. Both vehicles were also equipped with an IST tri-axial accelerometer, screwed to the floor of the vehicle near its center of gravity, which recorded x, y, and z acceleration at 3,200 hertz.

The majority of the data logging equipment available was installed on the Crown Victoria since it would contain the live driver. It was outfitted with a Tiny Data Recording System (TDAS) which has a data collection rate of 10,000 hertz. The TDAS has 24 data channels available and all were utilized with various inputs. Three tri-axial accelerometers were mounted on a head band around the driver’s head and this allowed for an approximation of the acceleration experienced at its center of mass. A tri-axial accelerometer was mounted to the driver’s thorax along with accelerometers on the lumbar spine measuring x and z accelerations. A tri-axial accelerometer was also mounted near the Ford’s center of gravity and monitored by the TDAS. The TDAS was also used to monitor the Restraint deployment signal (RDS) voltage from the ACM to the PCM. The ABS voltage and brake voltage was monitored at the fuse block. The child safety seat had a uni-axial accelerometer mounted on the seat, measuring the x-acceleration of the seat. A string potentiometer was attached to the brake pedal and measured the movement of the pedal. The string potentiometer voltage was recorded by the TDAS. A load cell was also mounted on the driver’s seat belt, measuring seat belt load, which again was recorded by the TDAS. A tape switch was attached to the front bumper of the Crown Victoria, which triggered the TDAS to start recording when tripped and also fired a pair of bright strobes which would show up on the in-car video. This was done so the videos of the test could be synced with the “time zero” of the TDAS. The TDAS recorded the GPS speed as reported by a VBOX Pro mounted in the Ford at 100 hertz. A Contour GPS high definition, 60 fps video camera and GPS data logger was installed which recorded the driver’s movement and the GPS coordinates of the vehicle.

A Hypertech Max Energy Programmer was used to alter the Ford’s PCM programming. The PCM was adjusted to show 38 inch tall tires, thereby providing a false and much higher speed reading on the PCM and speedometer.

The Hyundai Sonata was equipped with less instrumentation than the Ford. This was due to monetary and time constraints as well as the lack of a human subject in that vehicle. As mentioned, the Hyundai was equipped with an IST tri-axial accelerometer and Video VBOX Lite. The high resolution Video VBOX Lite camera was focused on the front passenger seat, with the belted dummy to record the motion of the dummy and potential airbag deployments. The low resolution camera was focused in the direction of the incoming Crown Victoria.

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Crown Victoria: Impact speed

28 mph

∆Vx

-15.7 to -16.6 mph (depending on instrumentation)

∆Vy

3 mph

∆t

153 msec.

Hyundai

Impact speed

9 mph

∆Vx

-15 mph

∆Vy

-11 mph

∆t

157 msec.

Table 1: Crash test data summary The Hyundai fired its frontal air bags but not its side air bags.

The Ford fired a seat belt pretensioner, but did not deploy its frontal air bag.

A

cceleration Data Analysis Acceleration data in G’s for the Crown Victoria was collected at both 3200 Hz and 10,000 Hz. The graph in Figure 1 shows a comparison of the collected x and y data. The data approximately overlays but the peaks are considerably different between the two data sets. This is due to aliasing of the lower frequency data caused by the difference in the collection rates. The lower collection rate data appears as a “filtered” version of the higher collection rate data missing some of the peaks seen in the high collection rate data.

The higher collection rate data is a better representation of the actual event but the average G values are approximately equal between the two data sets.

Acceleration data in G’s was collected at 3200 Hz for the Hyundai Sonata. A graph of that data is shown in Figure 2.

The magnitudes of the x and y accelerations are approximately equal due to the approximately 45 degree angle of impact for this crash. This impact triggered the frontal airbags but not the side bags. When examining the high speed video of this crash, the left rear tire initially lifted off of the ground and then dropped back down. The 2-Gs positive acceleration in the y direction at approximately 65 ms and subsequent oscillations in the y acceleration until approximately 120 ms appears to have been caused by the tire dropping back and bouncing the vehicle back towards the Crown Victoria after the initial impact. There also appears to be a matching positive peak in the TDAS x-acceleration data from the Crown Victoria seen in Figure 1, at approximately the same recorded time.

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rash timeline The timeline of the crash as defined by the Crown Victoria data collection is shown in Figure 3. This timeline has two different starts, or time zero events as shown in the Figure. There is the initial TDAS time zero which was defined by the tape switch on the front bumper, and the ACM algorithm start which is 31 milliseconds later. The ACM algorithm starts at a threshold delta V of five miles per hour (8 kph) while the tape switch activates at initial vehicle to vehicle contact. This difference explains the 31 ms offset in the two start

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Figure 1: A comparison of the collected x and y data for the Crown Victoria

Figure 2: A comparison of the collected x and y data for the Hyundai www.collisionpublishing.com

Collision Magazine 41

Figure 3: The timeline of the crash as defined by the Crown Victoria data collection times shown in the Figure. Downloaded CDR x-acceleration values overlay nicely with the measured TDAS x-acceleration values as shown. There is also good agreement between the delta V values from the ACM (-15 mph) and TDAS (-17 mph).

Once the ACM algorithm has completed (248 milliseconds or 279 milliseconds after tape switch activation) it shuts down the ten volt restraint deployment signal (RDS) feed to the PCM for 100 milliseconds as shown in the graph. The PCM locks data once the ten volt feed is seen again (RDS signal is voltage on) after that interval as indicated in the figure. Due to the PCM data collection rate (10 Hz), the actual PCM time zero could be anywhere within a 200 millisecond window of the RDS signal from the ACM. This means that the data may have to be shifted in time to properly match the ACM time zero.

Indicated vehicle speed is stepped in the graph because the data acquisition rate of the TDAS system is significantly faster than the output rate of the VBOX which supplied the speed indication to the TDAS in this crash.

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iomechanical data analysis The Crash Team biomechanical engineers were primarily interested in focusing on the Vehicle vs. Driver’s Biomechanical Response to the crash. More specifically, the focus was on the varying time delays or phase shift between the x-direction vehicle acceleration and the biomechanical responses of lumbar and thoracic acceleration in the x-direction.

In addition, the relationship between the shoulder belt load (thoracic restraint) and the induced angular acceleration of the head about the y-axis was also analyzed. This analysis was aided

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by the use of high-speed video which showed the discharge of a photo-flash unit representing the collision “Time-Zero” (as measured by the TDAS system bumper switch input) as well as the kinematics of the driver’s torso and head rotation. Finally, the x-direction acceleration at the front of an infant seat that was restrained at the right-side, rear seat was compared to the x-direction acceleration at the vehicle CG. Figure 4 is a graph showing the “Vehicle and Driver Response to Collision”. At “Time-Zero”, the graph illustrates the vehicle undergoing negative acceleration due to pre-impact braking (black). For the lumbar spinal area (red), there is an approximate 30 millisecond delay from the onset of the vehicle crash acceleration. Finally, after an additional 50 milliseconds, the thoracic region (blue) begins to exhibit the loading imparted via the shoulder belt. This general information provides a foundational understanding of the parameters required for consideration in airbag system design. More specifically, the amount of time between the onset of a collision pulse and when an airbag has to be inflated and ready to receive the impact loading of an individual’s torso, head and neck. .

Figure 5 is a graph displaying the tensile load measured at the shoulder portion of the seat belt webbing representing the restraint of the torso and the resulting angular acceleration imparted to the head. The initial trace of the head acceleration between approximately 50 to 75 milliseconds was due to contact of the accelerometers with the headrest. At approximately 75 milliseconds the shoulder belt tension is increasing

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Figure 4: Vehicle and Driver Response to Collision

Figure 5: tensile load measured at the shoulder portion of the seat belt webbing representing the restraint of the torso and the resulting angular acceleration imparted to the head www.collisionpublishing.com

Collision Magazine 43

Figure 6: The x-direction accelerometer responses of the Crown Victoria CG vs. the base of the infant car seat mounted in the right rear seat position which represents loading of the torso/chest. As a direct result, the neck is forced into flexion in-phase with the belt load and is represented by the negative angular acceleration trace of the head CG. As the shoulder belt load nears zero and the forward flexion reaches its maxima, the head rebounds, and begins to rotate backward represented by the positive values of the angular acceleration trace.

Figure 6 is a graph displaying the x-direction accelerometer responses of the Crown Victoria CG vs. the base of the infant car seat mounted in the right rear seat position. The traces are nearly identical without any appreciable offset in the response time or magnitude. This is representative of an appropriately mounted and restrained car seat in which the acceleration at the seat base approximately mirrors the vehicle acceleration. There is however a shift from negative to positive acceleration of the car seat at approximately 150 milliseconds from slight rebounding back into a marginally compressible seat back.

empirical analysis for vehicle crashes, particularly when a live test subject is available to drive one of the vehicles.

Overall, the ARC-CSI Crash Team Boot Camp was an exceptional opportunity to plan, execute, evaluate, analyze and present crash test data during a crash conference and the entire crash team would highly recommend the experience to anyone seeking a better understanding of crash analysis.

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onclusion A substantial amount of data was collected from this and every other crash which was done during the 2011 ARCCSI Crash Conference crash day. Only a small subsection of that data was evaluated for the presentation and this subsequent article due to time constraints. Hopefully further analysis and presentation of this data will follow. Crash testing continues to be an excellent source for 44

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CDR Trainers & Mentors Collision Publishing, in conjunction with Collision Safety Institute, has compiled the largest online directory of competent and professional certified CDR Technician Trainers. The CDR Trainers/Mentors listed in this directory have completed the most current certification training in the industry and are now licensed to teach the Collision Safety Institute’s Level 1 and Level 2 CDR Technician courses. If you need CDR Training, look no further, find a CDR Technician Trainer/ Mentor near you. www.

cdr-training.com Want to become a CDR Trainer/Mentor?

Register for the upcoming CDR Train the Trainer Course in Houston, TX January 19, 2012. www.cdrsummit.com

Intersection Crash Reconstruction from Cradle to Grave Terry D. Day

Engineering Dynamics Corporation (EDC) ntroduction The goal of a crash reconstruction is often oversimplified. The answer to the question “How fast were the cars traveling?” is not the goal of a reconstruction, rather, it is a means to the end. To be sure, vehicle speeds play a key role. But the main purpose of a reconstruction is to determine the cause of a crash. A second purpose, often equally important, is to determine if and how the crash might have been avoided.

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This article is a primer on the task of answering the two key questions to be addressed by the reconstruction: cause and avoidability. A sample crash is used to illustrate the entire process, from cradle to grave. This example is not a case study. Rather, it is a hypothetical crash which serves as a procedural template that may be used as-is, or extended as needed. escription of Crash Our sample crash occurred in a small, mid-western town on October 14th at 11:45 AM. Two passenger cars were approaching a controlled, 90-degree intersection. The 4-lane streets (2 lanes in each direction) were essentially flat and level. The east-west lanes were through traffic, while the northsouth lanes were controlled by stop signs. Sidewalks and small businesses lined both sides of the streets, as shown in Figure 1.

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A 2010 Ford Crown Victoria was traveling eastbound, while a 2005 Chevrolet Impala was traveling in the northbound (controlled) direction. The vehicles collided in the intersection and traveled in a generally northeasterly direction to their rest positions. Both 46

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vehicles mounted the curb at the northeast corner of the intersection. The Ford struck the corner of a building, bringing it to rest. A sketch from the police accident report is shown in Figure 2. The preliminary cause of the crash was attributed to the Chevrolet’s driver failing to obey the stop sign. This conclusion was supported by two witnesses.

The Chevrolet’s driver said he had stopped and pulled out, thinking there was plenty of time and distance available to safely cross before the Ford reached the intersection.

Q

uestions to Address The primary goal of the reconstruction was to confirm the cause of the crash. In particular, answers were required to the following questions:

• • •

Did the Chevrolet’s driver stop at the stop sign?

Was vehicle speed a factor?

Was inattention by either driver a factor?

A secondary goal, derived from the answers to the above questions, was to determine if the crash was avoidable, given the speeds and attentiveness of each driver.

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nalytical Approach The reconstruction of this crash follows a simple, straight-forward approach. Software may be used, but is not necessary. The laws of physics dictate the information required for the analysis. olice Accident Report The police accident report is usually the starting point for information gathering. It provides a generally unbiased view of the circumstances surrounding the event. This information includes:

P •

Basic Scene Information – Location of the crash site and basic measurements. The police accident report often includes a sketch of the site and a narrative describing the event.

•

Detailed Scene Information – In more severe crashes, the police accident report may include measurements of the crash-related artifacts (tire skid and/or scuff marks, gouge marks, as well as vehicle rest positions. In the most serious crashes, the on-scene investigation includes a total station survey with very detailed scene measurements.

•

Photographs – The police accident report for most injury crashes relies heavily on the use of photographs to document the crash site at the time of the crash. These photographs are important because much of the scene information is ephemeral (temporary evidence, such as fluid spills, faint tire marks and vehicles at their rest positions). Photographs may also be helpful later on for estimating important data parameters, such as tire marks or damage profiles, using photogrammetry. www.collisionpublishing.com

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Figure 1: Crash scene

Table 1: The required vehicle dimensional, inertial and tire data

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Figure 2: Drawing of crash scene

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•

Basic Vehicle Information – The police accident report typically includes the vehicle make, model and year. Vehicle properties are not normally included, but can be obtained based on the vehicle make/model/year information. If available, vehicle photographs provide additional documentation.

•

Witness Statements – Witnesses can provide valuable information to either support or refute the reconstruction. However, it is important to avoid using witness statements as the basis of the reconstruction. Doing so reduces the value of the reconstruction as an “independent witness based on forensic evidence and the laws of physics.” For this reason, limited emphasis is placed on witness statements until after the reconstruction is complete.

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ehicle Data The required vehicle dimensional, inertial and tire data are presented in Table 1. These data are sufficient for the analysis methods used in our reconstruction. For purposes of our study, we are going one step further: We have 3-dimensional models of our vehicles. This allows us to better visualize the event when it comes to our visibility study (see Time vs. Distance Study). This is also invaluable if the case is presented to a jury.

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cene Data For purposes of our reconstruction, we are using the results of a total station survey to create a scaled, 3-dimensional model of the crash site. Again, this 3-D model offers a significant advantage when it comes to our visibility study, and is invaluable if the case is presented to a jury.

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• • • • •

Table 2: The damage profile that was measured during the postcrash vehicle inspection

vent Data In order to calculate vehicle impact speeds, the following event-related information is required for each vehicle: Position at impact Position at rest Path between impact and rest Wheel lockups (drag factor) (see note at the bottom of the page)

To calculate the speed at the onset of braking requires the following: • Impact speed (above) • Position at the beginning of braking • Path between beginning of braking and impact • Wheel lockups (drag factor) To calculate speed change (delta-V) requires the following • Damage profile These data are required by the laws of physics, regardless of the analysis method or tools (i.e., hand calculation vs. computer software). Sometimes it is necessary to estimate certain parameters (e.g., rest positions), but in our case, the at-scene investigators documented the locations of tire marks, gouges and rest positions (see Police Accident Report). In addition, our vehicle inspections provided wheel lock-up information (see Vehicle Data).

Figure 3: The results of the damage-only analysis.

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Collision Magazine 49

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nalysis Our reconstruction analysis proceeds as follows:

•

A damage-based reconstruction analysis is used to provide the impact speed for the Ford when it hit the building.

•

A momentum-based reconstruction analysis is used to provide impact speed results for both vehicles. This reconstruction also provides begin braking speed for the Ford.

•

A simulation analysis is used to confirm the above speed estimates. The simulation also provides the time vs. distance study to be used as the basis for our next step.

•

Perception/reaction times are determined using the 3-D environment model and the time vs. distance study from the simulation.

•

The cause of the crash is determined from conclusions drawn from the above results.

•

Avoidability is determined using the above results and changing initial conditions (i.e., speed) and (possibly) perception/reaction times.

Table 3: The vehicle position data

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amage-based Analysis The Ford Crown Victoria struck a building at the end of its rollout after impact with the Chevrolet Impala. Normally, a damage-only analysis will not provide impact speed; scene data are required as well. But this case has an important exception: The impact with the building stopped the Crown Victoria. Therefore, its separation velocity is zero, so its delta-V is equal to its impact speed. Thus, a damage-only analysis will effectively give us the speed at impact with the building.

The damage profile was measured during the post-crash vehicle inspection; see Table 2. The results of the damage-only analysis are shown in Figure 3.

Since the impact speed is equal to the delta-V, its speed at impact with the building was 25 mph.

Table 4: The vehicle wheel lock-up data

NOTE: Damage profiles are required in a 2-vehicle crash reconstruction if the collision is collinear (nearly head-on or rear-end).

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omentum-Based Reconstruction Analysis Impact positions were estimated from tire skid and scuff marks measured at the crash site during the on-scene investigation. Rest positions were also provided by the on-scene investigation. Wheel lock-ups were estimated from post-crash vehicle inspections. Pre-impact tire marks were used to estimate the location of the Crown Victoria when its brakes were applied. The presence of tire marks suggests full braking. The vehicle position and wheel lock-up data used for the momentum-based reconstruction are shown in Tables 3 and 4, respectively. A summary of the results of the momentum-based reconstruction analysis is presented in Figure 4.

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imulation Analysis The results of the above reconstruction analysis provide some very important information: the speed and location of the Ford at the beginning of braking. For the 50

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Figure 4: A summary of the results of the momentum-based reconstruction analysis

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Chevrolet, we know the speed and location at impact speed. This information is sufficient for us to set up our simulation analysis.

We begin setting up the simulation by choosing an arbitrary position for the Ford before it began braking. Its initial position will be important for the time vs. distance study. If we choose, say 2.5 seconds before the onset of braking, given its prebraking speed of 40 mph (58.7 ft/sec), we would set the initial position of the Ford 146.75 ft (2.5 sec x 58.7 ft/sec) before its begin braking position.

We then apply full braking and, using trial and error, apply steering inputs that cause the vehicle to reach its impact position and orientation at a speed of 33.5 mph.

Next we assign the initial position of the Chevrolet. We will start by assuming constant speed; we can change this assumption later on as required.

Play the simulation. It shows us the Ford reached its impact position at t = 2.86 seconds. From our reconstruction analysis, we have the speed of the Chevrolet, 35 mph (51.33 ft/sec). So the initial position of the Chevrolet must be assigned a distance of 146.8 feet (2.86 sec x 51.33 ft/sec) before impact.

The post-impact wheel lock-ups are the same as we used in our reconstruction. We can now execute the full event and allow it to run to completion. The vehicle set-up data for our simulation analysis are shown in Table 5. The results of the simulation are summarized in Figure 5.

Table 5: The vehicle set-up data for the simulation analysis

T

ime vs. Distance Study Because a simulation analysis is performed in the time domain, it directly provides the time vs. distance study. In addition, the use of 3-D models for the vehicles and crash site allows us to actually view the crash from inside each of the vehicles. Thus, we can see when the vehicles became visible to each other, as well as when steering and braking were applied by the Ford’s driver. All we need to do is play the simulation forward and watch the results.

Initial visibility between vehicles occurred at t = 1.28 seconds (see Figures 6a and 6b). Continuing to play forward, we see the driver of the Ford began steering at t = 1.52 seconds (0.24 seconds after initial visibility), and began braking at t = 2.52 seconds (1.24 seconds after initial visibility).

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Figure 5: A summary of the results of the simulation

erception/Reaction Time The opportunity for a driver to avoid a crash begins when visibility of the other vehicle becomes possible. Therefore, the time difference between initial visibility and the beginning of the driver’s steering and/or braking inputs determines the driver’s maximum possible perception/reaction time. Those results for our crash are summarized in Table 6. Standard values for driver perception times and braking reaction times may

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Collision Magazine 51

Figure 6a: Ford driver's initial visibility of Chevrolet be found in the literature; see Table 7. The time vs. distance study shows that the driver’s response time was very quick when compared to typical drivers. There was no indication of inattention. In fact, the steering response time was so quick, it is easy to conclude that the driver was anticipating cross traffic before it became visible, a sign of an experienced, attentive driver.

Table 6: Simulation results

Table 7: Standard perception/ reaction times

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hevrolet Driver Did the Chevrolet driver obey the traffic control device (stop sign)? To answer this question, a new simulation event can be created for the Chevrolet with its initial position at the stop line, the initial speed equal to zero and 100% wide-open throttle.

The results of this simulation reveal that the maximum speed of the Chevrolet after traveling 44 feet from the stop line to its impact position would be 24 mph. Our reconstruction revealed the impact speed was 35 mph, much faster than the speed of the vehicle if it had stopped at the stop sign. Conclusion: The driver did not obey the stop sign.

To find the Chevrolet’s minimum speed as it entered the intersection, we can create an event just like the previous one, except increase the initial speed until the vehicle is capable of reaching the impact position at the established impact speed. The resulting minimum speed is 25. Note that this is a miniwww.collisionpublishing.com

mum. Any speed above this estimate (limited by impact speed) is possible.

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voidability Our reconstruction showed the Ford was traveling at about 40 mph when its brakes were applied. The speed limit was 25 mph. Was speed a factor?

To answer this question, we can create a copy of our original simulation event, placing the vehicles at their positions of initial visibility.

We then change the speed of the Ford from 40 mph to 25 mph and remove the brake application. All other parameters remain unchanged. Executing the event reveals that the vehicles would miss each other by about 24 ft. This is a near miss; still, the crash would have been avoided if the Ford were traveling at the posted speed. Any braking would increase the distance between the vehicles.

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onclusions • Both vehicles were exceeding the posted speed limit.

•

The speed of the Ford was a factor. The collision would not have occurred if the driver obeyed the speed limit. Although the collision would be avoided, it would still be a near miss.

Figure 6b: Chevrolet driver's initial visibility of Ford

D

•

Inattention by the Ford driver was not a factor. The driver was paying close attention and responded appropriately.

•

The Chevrolet driver did not stop at the stop sign.

The Chevrolet was traveling at least 24 mph when it entered the intersection.

•

The driver of the Chevrolet may have accelerated after entering the intersection, possibly trying to avoid the crash. This could not be confirmed.

•

The Chevrolet did not have sufficient room to safely enter the intersection.

iscussion The results of this reconstruction show that a reconstruction can yield much more information than simply the speed of the vehicles.

The time available for the Ford’s driver to perceive and react would increase slightly if, instead of assuming a constant speed of 35 mph in the time vs. distance analysis, the minimum speed for the Chevrolet, 24 mph, was used. The additional time does not affect the conclusions regarding avoidability and/or driver inattention.

Our analysis of perception/reaction time quickly revealed the Ford driver’s response was reasonable when compared to the literature. However, the subject of driver perception/reaction time is very complex, and is dependent upon several factors not directly addressed in this article.The results of a crash data recorder could be used to confirm the impact speeds, as well as

to provide the starting point for the remaining analysis (simulation, time vs. distance, avoidability).

Software is not required in order to perform this reconstruction. However, the computer simulation analysis provides a significant advantage. The time vs. distance, perception/reaction and avoidability issues are answered directly by viewing the simulation results. The simulation also provides a physicsbased animation of the crash that can be viewed by lay-persons.

A sensitivity analysis should be performed to provide a range of possibilities before drawing specific conclusions.

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eferences [1] Muttart, J.W., “Quantifying Driver Response Times Based Upon Research and Real Life Data,” Proceeding of the Third International Driver Symposium on Human Factors in Driver Assessment, Training and Vehicle Design, 2005.

[2] Olson, P.L., “Driver Perception Response Time,” SAE Paper No. 890731, Society of Automotive Engineers, Warrendale, PA 1989.

[3] A Policy on Geometric Design of Highways and Streets (AASHTO Green Book), 5th Edition, American Association of State Highway and Transportation Officials, Washington DC, 2004.

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Collision Magazine 53

Crash site evidenCe

A 2010 Chevrolet Equinox SUV attempted to make a left turn in front of a 2003 Dodge Ram pickup. The pickup was in the middle northbound lane when it struck the left-rear side of the SUV, causing both vehicles to rotate CCW to their final rest positions.

The right-rear passenger in the SUV suffered significant facial injury, but there was no physical evidence on the back of the right front seat. How did the facial injury occur?

For more information on the capabilities of HVE please visit edccorp.com

HVE directly answers the following questions using Newton’s laws of motion:

Questions

Answers

Impact Speeds

SUV: 22 – 25 mph Pickup: 42 – 45 mph

Peak Impact Force

SUV: Fx= -37,850 lb, Fy= 66,350 lb, Fz= -1,560 lb Pickup: Fx= -71,400 lb, Fy= -26,700 lb, Fz= 1,880 lb

Peak Impact Acceleration

SUV: 18 – 23 g Pickup: 12 – 15 g

Peak Angular Velocity

SUV:

~ -340 deg/sec

PDOF

SUV:

~ -61 deg

Occupant Analysis (Right-Rear)

Seat Belt Status: Unbelted General Motion of Occupant: Left/Forward Facial Contact Detected: Left Front Seat Headrest

Required Technologies

SIMON 3-D Vehicle Dynamics Simulation Model DyMESH 3-D Collision Model GATB 3-D Occupant/Pedestrian Simulation Model

Other software may claim to answer these questions. Have you closely evaluated their claims and the basis for their results?

To learn more about HVE and all of the available tools for crash investigators, call 503.644.4500 or visit www.edccorp.com. Our professional sales staff will help you get started using HVE today!

Knowledge = Power 7096-0820

Engineering Dynamics Company, LLC • 550M Ritchie Hwy #128, Severna Park, MD 21146 USA • Phone 503.644.4500 • www.edccorp.com

Crash Data Group prides itself on providing best of class customer service. As part of our commitment to all of our customers, Crash Data Group assists with managing the inventory of your CDR System, offering various shipping methods and times, and helping you identify what cables and adapters are needed for your CDR System.

Crash Data Group is the exclusive distributor for the Crash Data Retrieval product line. We offer new CDR System Kits, new release updates, replacement cables, CDR Software subscriptions / renewals and Pelican cases.

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cdr-system.com

NEW CDR SYSTEMS

Crash Data Group will help evaluate your needs for a new CDR System and help you choose the system that is right for your needs and budget.

NEW RELEASES or REPLACEMENT

Visit the Crash Data Retrieval website for information on the latest CDR releases or to browse the full CDR catalog of replacement parts.

INVENTORY MANAGEMENT

When you purchase from Crash Data Group, we keep detailed records of your hardware and software to better serve your needs.

Crash Data Group w (800) 280-7940 w www.cdr-system.com

APPLICATIONS OF GPS DATA IN

COLLISION RECONSTRUCTION

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Daniel J. Melcher, P.E. Rachel E. Keller, P.E.

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Jay J. Przybyla, M.S. Thomas N. Rush, ACTAR

bstract As sources of Global Positioning System (GPS) data increase in prevalence, it is important for collision reconstruction practitioners to understand how to apply this type of data within their reconstruction framework. Using GPS data requires an understanding of the different types of GPS data as some data sources have limitations that can lead to misapplications or incorrect conclusions. After obtaining or acquiring GPS data it must be analyzed to reach accurate and supportable conclusions regarding a specific collision event. Tying GPS data into other sources of collision evidence presents a challenge that can be overcome with careful analysis. The appropriate mathematical calculations and analytical procedures will be addressed using real world case experience. Additionally, the types of collision events that can best benefit from the context of GPS data will be discussed.

calculations to seek solutions to questions such as, “Where was Vehicle 1 when it left its lane?” “How fast were Vehicle 1 and Vehicle 2 traveling when they collided?” or, “Did Vehicle 2 brake prior to impact or after impact?” A number of methods have been developed over the decades to utilize data such as tire marks, vehicle damage profiles, and post-impact paths across surfaces. These traditional methodologies are all based on direct visual observation and measurement of the physical world, combined with calculation techniques to convert the observed evidence into distances, times, velocities, and accelerations.

In recent years, new types of Electronic Data Recorder (EDR) technologies have become available to provide additional information about vehicle positions in space and time. Many passenger vehicles contain Airbag Control Modules (ACM) or Powertrain Control Modules (PCM) capable of recording data related to a specific collision event. These ntroduction technologies utilize data collected from a vehicle’s At its most fundamental level, the science of colli- modern electrical systems, such as wheel speed sension reconstruction can be simplified as an attempt sors, roll sensors, or internal accelerometers, but to gather data in order to determine the position usually do not record any type of time data. In fact, in space and time of one or more objects. Tradition- the timing of data acquisition from the vehicle serial al collision reconstruction techniques use physics bus can be a point of debate or misunderstanding in a collision analysis.1 However, these types of EDR data have been validated and are commonly relied upon by professionals in the collision reconstruction community.2,3,4 Electronic Control Modules (ECM),

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Collision Magazine 57

which are readily available as part of the engines of many commercial motor vehicles, can contain information such as speed collected from a wheel speed sensor and the time of day the data was collected.5 However, this data usually is not accelerometer based and mathematical analysis is required to connect the data to a specific event in the time domain.6 These types of EDR data have been collected and validated in a number of peer-reviewed journal articles, and are commonly relied upon by professionals in the collision reconstruction community.7,8 Although potentially useful as data sources for a collision reconstruction, the ECM, PCM, and ACM technologies were all initially developed to collect and analyze data for non-collision purposes, such as supplemental restraint deployment, engine

sible until the 18th century development of a relatively precise chronometer and sextant combination for determining latitude and longitude. In 1957, the launch of Sputnik opened the possibility of using satellites for a variety of technological applications. Shortly thereafter in the 1960’s, one of the first uses of satellites was for a U.S. Navy submarine navigation system called TRANSIT.13 This approach showed promise, so in 1973 the first true global positioning system, NAVSTAR, was developed by the United States Defense Department. The first GPS satellite was launched in 1978, with the final of the current 23 satellites launched in 1990. A major shift in the exclusive U.S. defense use of the system occurred in 1983 after a plane carrying 269 people was accidently shot down after entering USSR airspace. President Reagan responded by allowing the first non-military and international use of GPS for air navigation. However, civilian applications remained largely impractical and imprecise until 2000, when the military stopped their program of “Selective Availability,” an intentional degradation of signal quality. In the decade since reliable GPS data became available, civilian use has expanded exponentially.

“” In the past decade, the Global Positioning System (GPS) has become another option for collision reconstructionists

performance optimization, and drivetrain operations. Because they were not explicitly intended for gathering data about vehicle position in space and time, mathematical manipulations of the data, such as extrapolation of distance from recorded speed and time information, are typically necessary to answer some of the important collision reconstruction questions.9 The time increment at which data is collected or recorded can range from milliseconds to several minutes, but time information is relative to a particular event rather than global time. Similarly, the speed information collected through ECM, ACM, and PCM technologies do not provide an exact location for where a vehicle was at any particular time. Scene data must be collected and correlated with the module’s information to coordinate the event data to a particular location or position.10 In the past decade, the Global Positioning System (GPS) has become another option for collision reconstructionists for gathering data regarding location, speed, and routes of both vehicles and individuals.11 Unlike the previously discussed technologies, GPS was specifically designed to determine and record an object’s position in space and time, providing valuable data. However, it is important to understand how the technology works and what information is being stored or recorded by GPS devices before the data gleaned from them can be properly applied to a collision reconstruction. Misunderstanding of the system, or of an individual device, can lead to misapplication or invalid conclusions, while attention to detail can produce a rigorous and robust collision reconstruction analysis.

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istory Civilizations have long searched for accurate and reliable ways to measure and document position in space and time.12 Reliable nautical navigation was not pos-

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echnology Each of the 23 satellites, weighing 2,000 pounds, orbits the earth two times a day at a height 12,000 miles above earth.14 They send a radio signal to Earth containing information about the satellite’s exact location and the time the signal was transmitted based on an on-board atomic clock. A GPS receiver somewhere on Earth typically collects these transmissions from at least four satellites. The time delays are calculated by the receiver for each of the satellites, which allows mathematically translation into three-dimensional spatial coordinates (latitude, longitude, and elevation) and one time coordinate.

The general technology of using GPS for determining and recording 3-dimensional spatial and time coordinates has been well proven. Military applications, including the Precise Positioning System (PPS), have been used successfully for decades of precision targeting. With augmentation, engineers and surveyors use GPS for field surveying in lieu of a laser-based total station. Automotive performance testing equipment, including equipment manufactured by VBox, uses augmented GPS technology to accurately and precisely measure and record vehicle positions and speeds to sub-centimeter, millisecond, and decimal velocity accuracies.15 Farm applications include guidance of tractors and other field equipment to optimize field coverage. Best known to the general public, millions of people utilize a GPS receiver to help them navigate their automobiles and boats, or use handheld devices for pedestrian guidance. These examples indicate wide acceptance of the technology in the public sector as well as the scientific community.

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ata Sources Because the GPS satellite broadcasts are available to anyone with a properly equipped digital receiver, many companies have developed a wide variety of devices incorporating some aspect of GPS. However, using the GPS signal does not necessarily mean that a device will record any data for review at a later time. Many devices only use the GPS signal in real-time and have no recording capability. Currently, the marketplace has introduced several products that do record some degree of GPS data that can be retrieved following a collision event.

Many technologies do not actually record the data within the vehicle or device itself, but rather upload position and time

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data to a central computer server. For example, a number of competing services attempt to improve the logistical performance of commercial vehicle fleets based on the concept of “Telematics”, the tracking of assets for decision making purposes. Systems such as QualComm, Xata, and PeopleNet utilize GPS for tracking the location of a particular load, the speed of the vehicle, and timeliness of the arrival of a given load. Some telematics systems are also able to transmit information from a “critical event” back to a dispatcher or to emergency services.

Data from a specific date, or from a critical event, may in some circumstances be available to a collision reconstruction professional for review.

data recording format is NMEA (National Marine Electronics Association) 0183 standard format.19 NMEA data is recorded in strictly controlled sentences that contain more than just positional information, such as the number of tracked satellites, satellite signal strength, confidence measures, Doppler speed, and error statistics. Because of the strictly controlled nature of the NMEA data format, some manufacturers have opted to use proprietary data formats, which typically record more fields than the NMEA format providing the user with more robust data. If an option is given as to which format the recorded data from a GPS device can be downloaded, the proprietary format should provide the best data.

Many emergency vehicles and dispatchers now utilize GPS for an understanding of how to best respond to an emergency situation and predict how long it will take to get there. Because of this application, police cruisers, ambulances, and fire trucks often have GPS data recorded at a central location that can be retrieved at a later time. Similarly, taxi fleets and transit vehicles often have GPS features that help dispatchers direct vehicles where they are needed and also aid travelers in acquiring realtime information about vehicle routes and arrivals. Passenger vehicles are sometimes equipped with units such as OnStar or BMW Assist, which provide in-vehicle GPS capability for vehicle tracking and emergency response notification.

The position information recorded in GPS data varies widely.20 While typical handheld and navigation GPS units are using specific latitude, longitude, and elevation, some reports only relate position as the nearest metropolitan area, nearest block, or nearest street address. In addition to the varying spatial reporting methods, the internal program of the GPS device can affect what type of data is recorded. In early GPS devices, Pseudo-Range (PR) readings were gathered from only four satellites and converted them into a 3D position. Modern receivers take the PR and Pseudo-Range Rate (PRR – which include the frequency error of the receiver’s clock and the Doppler shifts associated with motion) from all satellites in view for the associated sampling time and feed them into a single mathematical algorithm that produces an estimate of the position. The algorithm uses the combination of past and present PR’s and PRR’s from multiple satellites to improve the position estimates (Kalman Filtering). The result of the internal GPS algorithm is typically a smoothing of the location path resulting in data that is an estimate of position as opposed to the actual raw coordinates.

Other technologies do include recording capability within the device, including several products introduced specifically for the purpose of recording information related to a safety incident. For example, the DriveCam and IncarDVR devices are sold to private citizens for mounting in a personal vehicle to track and record onboard GPS data, which can be reviewed in case of a collision or event. Many similar devices are marketed to parents of teen drivers or others interested in monitoring driver performance. Taking this concept to the next level, Progressive Insurance has recently introduced a program where drivers can volunteer to have a GPS recording device installed in their vehicle in exchange for a reduction or adjustment in insurance premiums.

The most familiar forms of GPS device for the general public are the portable or permanent GPS receivers commonly placed in passenger vehicles for navigational purposes.16 As noted in previous literature, some portable GPS devices maintain a log or recording of the data utilized for the navigation in their internal memory.17 As technology develops rapidly, it is now quite common for cell phones and smart phones to contain a GPS unit or a hybrid geolocation technology based on a combination of cell tower, Wi-Fi, and GPS transmissions.18 Given the rapid pace of development in this technology, additional sources of GPS data are likely to grow in the future.

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ata Fields And Reporting Limitations Most GPS devices have the ability to show the current location, time, and position of the unit displayed in real time. Many devices also have the capability of recording information within the device or transmit the data to a central server for recording. When reports are generated from the recorded data, the report may include some or all of the data that was originally recorded and may be presented in paper or digital format. The information stored, transmitted, recorded, or reported depends on the type of GPS device used, specific settings within the device, and specifications of contracts between users and service providers.

Formats for stored GPS data can vary widely. In consumer GPS devices, position, time, and possibly other measures can be recorded and are called “trackpoints.” A more complete

Despite the removal of Selective Availability, and the development of advanced algorithms and Kalman filtering, there are still limits inherent within GPS signals that affect accuracy.

Some limit sources include Ionosphere and troposphere delays, signal multipath, receiver clock errors, orbital errors, the number of satellites visible, and satellite geometry and shading.

The Differential GPS (DGPS) and Wide Area Augmentation System (WAAS) technologies were developed to help counter some of the limits inherent in the GPS system by providing a ground based supplemental signal. A GPS that is WAAS capable can improve the accuracy of position data significantly.

Table 1 summarizes the accuracy expected for positional data for each GPS system.

Measure GPS System +/- 100 meters +/- 15 meters +/- 3-5 meters <3 meters

Original GPS with Imposed SA Program Typical GPS Position Accuracy without SA Typical Differential GPS Position Accuracy Typical WAAS Position Accuracy

Table 1: Published accuracy for various GPS systems.

Because position is calculated based on very small differences in time between several satellites, extremely precise timekeeping is required. If the clock was off by just a microsecond, the resulting error could be hundreds of feet. GPS satellites are equipped with cesium atomic clocks which are accurate to within 1 second in 100,000 years. Atomic clocks are very expensive, so consumer GPS units use “quadrangulation” for synchronizing to the satellite’s clocks. If the triangulation that is calculated from three satellites does not match the location calculated by a fourth satellite, then the GPS unit uses the fourth satellite as a correction factor to determine the correct timing.

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Collision Magazine 59

The signal timing will be adjusted until all four satellites agree on a signal correlation, resulting in the correct timing and therefore, an accurate position. The net effect is that GPS is recorded on a synchronized global timing system with extreme precision greater than microseconds. However, data reports rarely reflect this precision. Logistics and telematics applications often report to the nearest minute, and most navigation units report only to the nearest whole second or occasionally tenth of a second.

The rate at which a GPS system gathers information (“ping rate”) from the satellites is a significant factor. Logistics and telematics GPS units often ping for a location infrequently, such as every minute when moving and every 15 minutes when stopped. Most modern navigation GPS units display current location, time, and speed data on their screen. To accomplish any sort of reliable dynamic speed measurement, the sampling rate needs to be high. Reporting information at speeds of 60 mph at a rate of 0.1 Hz would mean that a new reading will be displayed each 880 feet. This sampling rate is much too slow for effective navigation as a user is likely to pass their intended turn before the unit has updated its position. Most commercially available GPS units sample at 1 Hz or greater.

As mentioned earlier, however, the rate of data and the precision of data actually recorded, or ultimately included in a report, may differ from the ping rate or extent of accuracy used by the device in its operation. In collision reconstruction applications, before GPS data can be analyzed, the recorded information needs to be accessed. Whether downloaded from a central server or imaged directly from a GPS unit, how and what data is stored and downloaded will have important implications in how the data should be interpreted. If the raw data is downloaded, a computer program will be needed to interpret the sentences and extract useful information, such as with NMEA format. If the data is in a proprietary format then proprietary software provided by the GPS manufacturer will be needed to read the data. In most circumstances, the reader will not be privileged to the raw data, but instead will have access only to the format presented in the program. For example, time might have actually been measured in the device to decimal parts of a second, or location may have been determined with 3 or 4 digits after the decimal point, but when displayed in a report the values are truncated to whole numbers.

In addition to the raw data of coordinate position and time, reports may display other data such as bearing, course, leg length, leg speed, elapsed time, max speed, etc. These are actually calculated values mathematically derived from the original coordinate and time data, and should not be confused with accelerometer, speed sensor, or other means of direct measurement. Consideration should be given to the accuracy, origin, and application of this data. For example, the leg speed can be reported as the speed at the beginning of the leg, end of the leg, or average speed across the leg. It may also be reported as 2D velocity only. Some programs report only a “maximum speed” for the leg, which if misinterpreted could suggest an inaccurate conclusion in a collision reconstruction application.

Testing and research journal publications have documented the precision and accuracy of some GPS device types. For example, GPS navigation units without WAAS augmentation have been validated to +/- 0.9 mph, while GPS navigation units with WAAS augmentation have been validated to +/- 0.5 mph.21,22 The published precision of +/- 3m in position for certain GPS navigation units has been validated by testing as well.23 Although not every device has been directly validated by independent research, the available literature has consistently 60

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supported the claims of manufacturer specifications for position and speed.24

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athematical Considerations GPS data does not always inherently provide distance information, so it must be determined from the position coordinates. Graphical applications, such as Google Maps, can provide rough estimates of the distances between two coordinates. Hand-calculations can be completed for greater precision, using the constant radius assumption known as the “Great Earth” formula. For points in latitude and longitude the distance between two points is defined as

When even greater precision is desired, ellipsoid models of the earth’s radii are cumbersome for hand-calculation but free calculator websites are available on the internet.25 Once the length of each individual leg is known, distance-time lines can easily be created by summing the leg lengths and leg time intervals.

There are two ways to determine the speed of a GPS unit, (1) indirectly from positional data differences and the corresponding time differences, and (2) Directly from the instantaneous Doppler speed, which is considered more accurate. A review of instantaneous speed and average speed is important when examining the differences. Consider an object moving along a path P that travels a distance ∆l=l2 - l1 during a time interval ∆t=t2 - t1. The distance traveled between two 3-dimensional points is defined as

The instantaneous speed of the object is defined as

The average speed

over time T is defined as

In the absence of Doppler speed measurements, the calculated speed must be an average speed across a leg. The shorter the time period for the leg, the closer the average speed will be to instantaneous speed, and the more precise the distance measurement is the more precise the speed calculation will be. The reporting rate and quality of the data will thus be the limiting factor in how accurate position based speeds can be.

Relationships between distance, velocity and acceleration can be used to extract more relevant information from the above data.26 The following equations relate distance, velocity and acceleration

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Since time intervals and distance intervals can be acquired or calculated from GPS data, useful knowledge about velocities, accelerations, and distance-time lines can be acquired. The caveat for this method is that the data is entirely dependent on the accuracy of the position data. Since every GPS position reading has a small amount of uncertainty, it is important to consider that uncertainty in collision reconstruction calculations. For example, over longer distances an accuracy rating of +/- 3m is unlikely to affect the conclusions reached. For very short distances, however, an accuracy rating of +/- 15 m could cause critical mistakes in analysis and conclusions. One major consideration is for lateral positioning of vehicles. A GPS that is set to “on-road only” will try to alter its position reporting to keep a vehicle “on the roadway” within its design constraints.

This may give “jumps” in data when a vehicle has left the roadway and the GPS does not update if off the roadway for some time.

Modern GPS units can use an alternate method of determining speed by using the Doppler effect. These GPS devices use a phase-lock loop receiver to continuously track carrier frequencies of a number of satellites. The difference between the known satellite frequency and the frequency at the receiver is known as “Doppler Shift.” Doppler Shift is directly proportional to the velocity of the GPS unit. With multiple satellites, it is possible to determine the 3D velocity vector of the receiver. This methodology has been validated to provide 0.01 m/s resolution and have 0.1 m/s accuracy.27,28 Analysis of collision events frequently requires extrapolation, where a variable’s value over time is projected outward from the first or last known data point. This is particularly true for precollision analysis as vehicles approach a collision location. GPS data by its inherent nature more often requires interpolation, where a variable’s value over time is projected in between two known data points. Interpolation is more robust than extrapolation since it has two known values on either side of the interval, but care should be given to the potential for fluctuation and variability rather than assumptions of either constancy or a straight-line function. Clearly, the interpolated values are most strongly supported when the time or distance interval is shorter. However, longer intervals have an offsetting benefit of precision, since the known position measurement range of +/3m is less significant over a distance of thousands of feet than over a distance of only several dozen feet.

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pplication Types There are an infinite variety of collision scenarios that may become the basis of a criminal investigation, insurance claim, or litigation case. Many such scenarios involve questions of position, time, speed, or acceleration, making GPS data a potential source of useful analysis.

It is important for any spatial application of GPS data to be able to integrate with traditional collision reconstruction scene diagrams and plot coordinate positions relative to the roadway geometry and collision evidence.

potentially help evaluate the specific position in space for an individual vehicle.

Presence Or Absence: In scenarios such as “phantom vehicle” incidents, hit and run collisions, or other events where one of the vehicles has not been identified, GPS data tracking records can help confirm or conclusively deny the presence of a specific vehicle, or an entire fleet of vehicles, at the known location and time of a collision.

Relative Position: In multiple-vehicle collisions, it is often initially unknown what order the vehicles were in before the sequence of collisions ensued. Similarly, vehicles may have been moved from the roadway to a shoulder area before investigators have arrived, raising doubt about which vehicles were in front or behind the others at final rest. GPS coordinate data could potentially help answer these relative position questions.

Stopped Or Moving: In many collision or near-miss events, there may be debate about whether a vehicle was stationary or moving slowly. Especially in collinear collisions where the speed of one of the two vehicles is needed for momentum calculations, GPS data for one vehicle may provide insight to help mathematically resolve the speed of the other non-GPS equipped vehicle as well. Another application is for stop signs and red traffic signals, and whether or not a vehicle came to a complete stop before entering the intersection.

Speed: Depending on the type and quality of the GPS data, information may be available to help determine the travel speed and heading of a vehicle at the time it became involved in a collision, or at some other discrete point in time and space. This is most important as an auxiliary support to a traditional collision reconstruction, where it can provide an additional method to confirm mathematically calculated travel speeds. GPS data may also provide information about vehicle speed at points in advance of the first available physical roadway evidence, such as for a vehicle that brakes at less than full lockup resulting in no visible skid marks. However, it is critically important to understand the source and detailed description of exactly what speed information is being reported by the GPS data.

Acceleration And Deceleration: By evaluating the rate of change of speed, or the second derivative of position with respect to time, a collision reconstructionist may be able to gather useful insight about the driver and vehicle performance throughout a collision event scenario. For example, if sufficiently precise and frequent data is available, the rate at which a vehicle accelerates from a stop into an intersection can be measured and evaluated in comparison to common values obtained through testing and observational studies. Similarly, the rate of deceleration can be evaluated to determine if a driver has applied light, moderate, or full braking, or to evaluate the mechanical performance of a vehicle’s brake system. The actual deceleration rate of a skidding, sliding, or overturning vehicle can be compared to other sources of friction information to support a reconstruction.

Based on past case experience, there are several categories of collision reconstruction assignments that have benefitted from GPS data review:

Distance / Time Lines: Once a vehicle’s position, velocity, and acceleration profiles in time have been determined, diagrammatic visualization of the distance-time path is often a valuable tool in evaluating collision scenarios. When both vehicle’s paths can be determined, issues such as available sight lines and closing velocities can be analyzed.

Location: At its most fundamental, GPS data can determine where a collision actually took place when there is uncertainty from other sources, or can help an investigator quickly find the locale for surveying and measurement of scene data. It can also

Driver Performance And Avoidance: GPS data analysis can help answer two fundamental questions related to driver performance. A review of the changes in speed and acceleration can provide insight into what the driver actually did as the poten-

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Collision Magazine 61

tial collision scenario unfolded. Analysis of the distance-time lines for all vehicles can help evaluate information available to drivers, and whether a driver performed reasonably given the information, distance, and time available to them.

10. Horak, D., “Estimation of Vehicle Speed and Trajectory Based on Video from a Vehicle-Mounted Camera”, Collision Magazine, Volume 4 Issue 2, 2009.

Context: Depending on the collision scenario, a set of GPS data may reveal information about the big picture leading up to a crash event, such as the route traveled, the hours of service for a commercial vehicle driver, or a pattern of erratic driving behavior.

12. James, R., “A Brief history of GPS.” TIME Magazine, 05/26/2009.

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onclusions And Further Research Careful consideration should be made when analyzing GPS data for collision reconstruction. Proper application of the data can provide the opportunity for robust and profound collision reconstruction analysis. Alternately, misunderstanding the information, how it was obtained, or how it is presented can lead to faulty conclusions about what and when events actually occurred. For this reason, GPS data should not replace traditional accident reconstruction techniques, but should be considered a supplement to other proven scientific approaches. In circumstances where no other information other than GPS data is available, critical review is important to reach valid conclusions.

As the technology of GPS devices has developed rapidly in the past decade, there are many opportunities to investigate and validate the different types of devices. New devices and software systems are likely to be introduced in coming years, making it important for the collision reconstruction professional to stay up to date.

R

eferences 1. Bare et al., “Analysis of Pre-Crash Data Transferred over the Serial Data Bus and Utilized by the SDM-DS Module”, SAE 2011-01-0809, Society of Automotive Engineers, 2011.

2. Ruth et al., “Accuracy of Powertrain Control Module (PCM) Event Data Recorders”, SAE 2008-01-0162, Society of Automotive Engineers, 2008.

3. Bortolin et al., “Chrysler Airbag Control Module (ACM) Data Reliability”, SAE 2010-01-1002, Society of Automotive Engineers, 2010.

4. Wilkinson et al., “The Accuracy and Sensitivity of 2003 and 2004 General Motors Event Data Recorders in Low-Speed Barrier and Vehicle Collisions”, SAE 2005-01-1190, Society of Automotive Engineers, 2005.

5. Ruhl et al., “Numerical Methods for Evaluating ECM Data in Accident Reconstruction and Vehicle Dynamics”, SAE 2003-01-3393, Society of Automotive Engineeers, 2003.

6. Messerschmidt and Muttart, “A Statistical Analysis of Data from Heavy Vehicle Event Data Recorders”, SAE 2009-04-20, Society of Automotive Engineers, 2009.

7. Goebelbecker and Ferrone, “Utilizing Electronic Control Module Data in Accident Reconstruction”, SAE 2000-010466, Society of Automotive Engineers, 2000.

8. “van Nooten and Hrycay, “The Application and Reliability of Commercial Vehicle Event Data Recorders for Accident Investigation and Analysis”, SAE 2005-01-1177, S 2005.

9. EDR Analytics, Messerschmidt Safety Consulting Inc. 62

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11. Clark, T., “GPS determination of Course and Speed”, http://www.aprs.net/vm/gps_cs.htm , accessed 5-20-2011

13. Navstar GPS Space Segment, “Navstar Global Positioning System Interface Specification IS-GPS-200”, March 2006.

14. Misra and Enge, “Global Positioning System: Signals, Measurements, and Performance”, Ganga-Jamuna Press, 2001.

15. Butler et al., “Using GPS Based Data Acquisition in Forensic Accident Reconstruction”, Collision Magazine, Volume 2 Issue 2, 2007.

16. Gpsinformation.net, “Garmin’s Data Field Definitions”, http://gpsinformation.net/gpsfields.htm, accessed 5-20-2011 17. Reust, T., “Vehicle Navigation GPS Units Could Be The Overlooked EDR”, Collision Magazine, Volume 5 Issue 2, 2010.

18. Scheck, J., “Stalkers Exploit Cellphone GPS”, Wall Street Journal, 08-03-2011.

19.Van Graas et al., “Precise Velocity Estimation Using a Stand-Alone GPS Receiver”, Proceedings of ION NTM, 2003.

20. Chalko, T., “Estimating Accuracy of GPS Doppler Speed Measurement using Speed Dilution of Precision (SDOP) Parameter”, Natural University Journal, 2009.

21. Witte, et al., “Accuracy Of WAAS-Enabled GPS For The Determination Of Position And Speed Over Ground”, Journal of Biomechanics 38, 2005.

22. Witte et al., “Accuracy Of Non-Differential GPS For The Determination Of Speed Over Ground”, Journal of Biomechanics 37, 2004.

23. Reust, T., “GPS Navigation Units: Recorded Data for Use in Accident Reconstruction”, Collision Magazine, Volume 6 Issue 1, 2011.

24. Fuchs, M., “Handheld-GPS based Speed-Measurements”, www.gps-speed.com, 2007.

25. National Oceanic and Atmospheric Administration, “Inverse Computation”, http://www.ngs.noaa.gov/cgi-bin/Inv_ Fwd/inverse2.prl, accessed 05-20-2011.

26. Serrano, et al., “A Single GPS Receiver as a Real-Time, Accurate Velocity and Accelerator Sensor”, Proceedings of the ION/GNSS, 2004.

27. Chalks, T., “High Accuracy Speed Measurements Using GPS”, Natural University Journal, 2007.

28. Sokolova et al., “Doppler Rate Measurements in Standard and High Sensitivity GPS Receivers: Theoretical Analysis and Comparison”, 2010 International Conference on Indoor Positioning and Indoor Navigation, 2010.

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Accident Reconstruction Photogrammetry Using Zoomed Images from Digital Cameras Lee DeChant J Rolly Kinney P.E.

I

mages that were zoomed from consumer grade digital cameras are often the only source of evidence for accomplishing measurements related to vehicle collisions.

It is well known in close-range photogrammetry (CRP) that when the camera’s lens is zoomed, the lens distortion values change and are generally unknown, making accuracy of the computed XYZ points prone to error. The traditional method of working with zoomed digital camera images has been solving the cameras inner parameters and exterior orientation, if enough 3-D control points are present in the images.

This traditional process of solving the camera’s parameters for zoomed imagery is usually labor intensive, and most reconstruction practitioners have found the process difficult to accomplish and only use it as a “last resort”.

This article discusses a new camera calibration computational algorithm called “Zoom-Dependant” (Z-D), that affords a reconstruction practitioner the option of using zoomed imagery through the standard process of reference marking perspective view images. Z-D metrically calibrates the digital camera throughout the entire telephoto zoom range, making the full capability of modern digital cameras easily accessible for accurate photogrammetric mensuration. Z-D corrects for the lens distortion, principal point offsets and focal length. Described in this article, are the requirements for calibrating, together with a comparative study of consumer grade Digital 68

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Collision Magazine 69

Single Lens Reflex (DSLR) cameras and Point and Shoot (PAS) cameras, metrically calibrated using iWitnessPROTM. Accuracy tests of the study are accomplished using the front end of a 1986 Porsche Carrera. The Z-D data are compared to a reference control network. Additionally, photogrammetric processing of zoomed imagery using only the EXIF (meta tag) focal length to characterize the camera was also used for comparison.

I

ntroduction Z-D camera calibration is expected to open up many new opportunities working with digital camera images that were zoomed, and not initially intended for photogrammetrical analysis. To date, the constraint of working with images of known camera parameters meant the camera’s lens was typically calibration at a fixed focal length, prior to accomplishing the computer analytics within the Close-Range Photogrammetry (CRP) software. In the case of imagery zoomed from a telephoto lens, the “zooming” also changes the lens distortion parameters and usually makes the photogrammetric data much less accurate than image analysis based on metric camera calibration.

The Zoom-Dependent (Z-D) process described eliminates the fixed focal length requirements that have been traditionally assumed in CRP software programs.

The CRP calibration software solves for the interior orientation properties of the camera and lens combination automatically from the imagery of calibration targets yielding the Focal Length; Xp, Yp Principal Point Offsets; and K1, K2, and K3 radial lens distortion coefficients. So the application of Z-D analysis can extract the coordinates of important feature points from images sets that could not otherwise be solved, would require much more effort if the solution was possible, and the resulting accuracy will be significantly better than solutions using only the EXIF focal length with no correction for lens distortion.

O

verview of Zoom-Dependent (Z-D) camera calibration The zoom-dependent calibration process models the variation of camera calibration parameters as functions of the nominal zoom focal length shown in the EXIF header of the image file. The functions describe variations in the interior orientation parameters of principal distance and principal point offset, and in the coefficient of the cubic expression utilized to model radial lens distortion. For most lenses the function is a power curve but linear functions are needed for some lenses. The interior parameters are interpolated from the calibration functions for the focal length shown in the EXIF file of each image. The Z-D calibration range includes four zoom/focus settings, nominally the widest and narrowest fields of views, plus two intermediate settings about equally spaced within the range.

P

hotogrammetric Study using Z-D The goal of the study was to compare different DSLR cameras and PAS cameras to a control network. In the study, four different make/model PAS cameras and two different model DSLR cameras (total 3 DSLRs) were employed in the field work. The 3-dimensional coordinates and residuals of all photogrammetric networks were compared to a control network established from a self-calibrated Olympus E420 with 14-42mm lens, with lens fixed to 14mm and manually focused to infinity.

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Seven cameras were calibrated for this study using the Z-D process: 1. (Qty 1) Olympus E-420 DSLR with 14-42mm lens set to 14mm – [This was the photogrammetry reference device and was calibrated only at 14mm.]

2. (Qty 2) Olympus E450 DSLR with 14-42mm lens, at 10 megapixels 3. (Qty 2) Kodak C142 “Easyshare” PAS, at 10 megapixels 4. (Qty 1) Nikon S510 “Coolpix” PAS, at 12.2 megapixels 5. (Qty 1) Canon SD 1300 IS “Powershot” PAS, at 12.1 megapixels The steps in the study described here were: 1. Accomplish Z-D calibration for each of the cameras at four different focal lengths.

2. Capture one or two image sets of the vehicle with each camera.

3. Process the imagery from the cameras with iWitnessPRO to obtain the network of selected points for: a. The fixed lens (control network) for the E-420 imagery as the reference in the study. b. The Z-D network based on the Z-D calibration of the image camera. c. The network based on the EXIF focal length only. d. The Z-D solution based on the Z-D calibration, but used on the images of an exemplar camera of the same make/model. e. The FOOM (Focal length From One Image) process used to orient the camera(s) and solve the network.

4. Compare the Z-D Network solutions to the E-420 Control Network solution on the basis of the RMS errors and also the error range of 3D affine coordinate transformation.

T

he Z-D Calibration Procedure To Z-D calibrate a camera with a zoom lens, four different focal lengths are required; the widest field of view (FOV), two other intermediate focal lengths, and the Narrowest FOV. The Z-D calibration is usually more accurate when the Auto-Focus is turned off –when the camera has the ability to turn the focus to a manual setting. Most PAS cameras do not allow the focus to be manually set, so the PAS camera is typically calibrated and used in the Auto-Focus Mode. Precise intermediate focal lengths zoom chosen for the Z-D calibration are not important, and should be about equally spaced between the Widest and Narrowest FOV’s. For example, if a PAS camera has a zoom range of 5mm to 20mm, advancing the cameras electronic “zoom slider bar” about one third and also two-thirds from the lens’s widest FOV, is a good practice.

The first step in the Z-D calibration procedure was to obtain about 12 images for each focal length, from strong perspective camera viewpoints, of a target array attached to a vertical wall surface over an area of about 5’ high x 8’ wide. Figure 1 illustrates the Z-D calibration target array used in this study. The camera’s onboard flash was required on all Z-D calibrations for automatically marking the red coded targets. A few coded

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Figure 1 – Z-D calibration targets for DSLR and PAS cameras targets were mounted off the plane of the wall to improve the initial relative-orientation process of the cameras during calibration. The maximum distance of the camera to calibration target array was about 24’ for the Narrowest FOV images.

After the four Z-D calibrations for a camera had been completed, a new project was opened in iWitnessPRO and the four camera calibration project files imported, e.g. “project1.iwpro” through “project4.iwpro. iWitnessPRO automatically computed the Z-D camera description from the four focal length projects. Figure 2 shows the Z-D calibration data displayed for the Olympus E420 w/ 14-42mm lens, with the power curve

The next step in the study was to open each set of camera images in iWitnessPRO and obtain the camera calibration for the set using fully automatic coded targets (specialized red/black dot placards).

Also shown in Figure 1, adjacent to the coded targets, were six printed 8.5” x 11” sheets with a quantity of three, 1.25” black dots. These relatively larger black dots were needed for PAS camera images when the telephoto zoom was set in the Intermediate 2 and Narrowest zoom settings, because the reflective red-coded targets could not be automatically detected and measured due to ‘target image blooming’ from the camera’s onboard flash. iWitnessPRO automatically “Z-D calibrated” the DSLR cameras successfully, measuring the red coded targets for all four focal lengths. The PAS cameras worked satisfactorily for automatic measurement in the Widest FOV and Intermediate 1 FOV focal lengths; but the Intermediate 2, and Narrowest FOV’s required user-assisted measurement through photogrammetric referencing of the paper sheet’s black dots. The Z-D calibration for each image set was saved as a unique project.iwpro file for the corresponding camera and lens setting.

Figure 2 – Z-D calibration dialog box with computed results for the Olympus E420 www.collisionpublishing.com

Collision Magazine 71

Figure 3 – Z-D calibration dialog box with Linear-ZD computed result for the K1 distortion shown on the left. The Z-D calibrated camera was then named a ‘unique ID’ and saved for later use on projects that utilize the specific camera. If a camera doesn’t employ in-camera lens distortion correction, the Z-D calibration is based on the Power-ZD mode.

In the event the camera has in-camera lens distortion, the user needs no prior knowledge of the camera’s “distortion correction” before the Z-D calibration process. iWitnessPRO determines this automatically, immediately following the importation of all four Z-D calibration networks. Figure 3 shows the Z-D dialog for the Canon SD 1300 IS Powershot that utilized in-camera lens distortion correction. The line at the bottom of the figure was not a proper fit to a power curve, so iWitnessPRO ‘forced’ the calibration to follow the Linear-ZD model, and the screen displayed a message that the mode had been switched.

N

etwork Measurement of the Porsche 911 Vehicle To compare the capability of various cameras and Z-D calibrations on a small scale project, targets were placed on and around the vehicle, and image sets were captured. Imagery was obtained with each camera, and then processed in iWitnessPRO, for various calibration schemes,

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and the results compared to the 3D coordinate positions of the Control Network obtained with the fixed lens Olympus E-420 camera.

The first step was to create a control network of the 3D points by applying around the front end of the vehicle with adhesivebacked passive-style red photogrammetric strip tape and single dot targets on the bumper, hood, and windshield illustrated in Figure 4. Three precision scale bars were used; two scale bars were placed on the ground in front of the vehicle, and one scale bar, was tripod mounted and placed on the vehicle’s roof.

Twenty-eight coded targets were randomly placed on the vehicle and fanned-out on the ground (mostly in front of the vehicle’s front bumper).

A total of 91 targets on the vehicle were measured for each network; but for this study only a subset of 19 spatially separated XYZ points were the basis for the tables presented.

The second step was to record images with each study camera from four camera positions, where all the cameras positions and camera aim points were generally the same locations for all of the measurement networks. The minimum intersection angle was approximately 40 degrees, while the maximum was

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Figure 4 Vehicle Target Pattern

70 degrees for all computed 3D points. For Z-D testing, the lens was a different focal length in all four camera positions used, with one of the four being at the lens widest FOV. The control network was obtained with an Olympus E420 with 1442mm lens, from twenty-three camera stations and a mix of both landscape and portrait orientation shots. iWitnessPRO processed twenty-three images in the E-420 control network in approximately 60 seconds, computing a quantity of 315 object points (i.e., the temporary applied red-dot passive targets and coded targets).

Location

Point Name

Front Bumper (Passenger side)

C1

Front Bumper

C2

Front Bumper

C3

Front Bumper

C4

Front Bumper (Drivers side)

C5

Hood Leading edge

T2

The imagery for each study camera was processed as a Z-D Network. In addition, one E-450 Network and one Kodak C142 Network were each computed using the Z-D calibration for the other camera of the same model. All targets on the hood were manually referenced in iWitnessPRO, but referencing was fully automatic ‘target centroid’ measurement for all other red/black synthetic targets that were applied.

Hood Leading edge

T3

Hood Leading edge

T4

Hood Leading edge

T5

Hood

T6

Hood

N8

Finally, comparisons were made between the vehicle results.

The E-420 control network, with an internal accuracy estimate of 0.006” RMS, (or 1:18000 of object size) was used as the reference base. The object space “check distance” (scale bar) satisfactorily agreed with the internal measurement estimates within the control network. The coordinate system was defined from one of the codes on the ground, adjacent to the passenger front tire and all Z-D and EXIF networks were later placed into the same coordinate reference system by using the least squares coordinate transformation feature called “Transformation to Control” within iWitnessPRO.

Hood

N10

Hood

N11

Hood

N9

Hood

T7

Windshield Base Center

T20

Windshield Upper Passenger side

CP7

Windshield Upper Center

T1

Windshield Upper Driver side

CP8

Figure 5 (right): The 19 points of the E-420 Control Network www.collisionpublishing.com

Collision Magazine 73

Six networks were evaluated for the two Olympus E-450 cameras, seven networks for the two Kodak C-142 cameras, two networks for the Nikon S510, and two networks for the Canon SD 1300IS. The Olympus E-450 lens were zoomed to the “tick-marks” on the lens body for the widest FOV at focal length 14mm, plus approximately 20mm, 25mm and 30mm.

The two Kodak C142 Easyshare cameras displayed an electronic zoom slider bar (through rotating the optical zoom lever), that was subjectively adjusted to “set” intermediate focal lengths at 6mm, then approximately 9mm and 14mm, plus the narrowest FOV at 17mm.

The Nikon Coolpix S510 zoom control was similar to the Kodak, and was set at approximately 5mm 8mm, 10mm, and 17mm.

The Canon SD1300 IS Powershot was set to four focal lengths of approximately, 5mm, 8mm, 14mm, and the narrowest at17mm.

One image set for each test camera was processed with the iWitnessPRO software using the Z-D camera calibration and a second image set using the ‘approximate’ focal length as read from the image EXIF meta tag. Both the Z-D and EXIF networks were then compared to the Olympus E420 Control Network as a measure of accuracy. Comparison between the Z-D and EXIF networks illustrate the difference of zoomed imagery from a metrically calibrated camera versus zoomed imagery from a non-calibrated camera.

The networks from the pairs of exemplar cameras, the two Olympus E450 DSLR’s and the two Kodak C142 PAS cameras, represent a situation where the camera that captured the available imagery cannot be obtained for Z-D calibration but an exemplar camera can be. Comparison of the networks obtained using the camera that captured the imagery, but using the Z-D calibration for an exemplar camera illustrates the variation possible among PAS and DSLR cameras of the same model.

L

ack of EXIF information In some situations digital images are the only evidence of a vehicle or scene and the EXIF meta tag information does not exist in the file. The only reliable approach to determine the camera’s inner orientation parameters is the traditional process of solving for the camera absolute orientation (i.e., back-calculation of the camera position and camera aim through measurement of known control points). The FOOM (Focal length From One Image) function in iWitnessPRO is one proven method to obtain the camera absolute orientation.

An example of the FOOM process is included here using the four images from one of the Kodak C142 cameras, with their EXIF data removed, making the images appear to be from “unknown” camera(s)). FOOM requires independent knowledge of the XYZ coordinates of eight or more points in each image in order to solve the focal length, principal points and K1 radial distortion. Marking and analysis of the FOOM network typically requires about twice as long as compared to a Z-D network.

The first row of each coordinate comparison table shows the RMS Error (in inches) for all the points in the network, expressed as residual vectors in the X-Axis (VX) Y-Axis (VY), and Z-Axis (VZ) columns, and the Total RMS error under the “Discrepancy Vector” column. The second row in each com-

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parison table shows the Error Range (inches) of the 3D affine coordinate transformation (read from the iWitnessPRO “3D Transformation to Control” dialog). The coordinate system was defined relative to one of the iWitnessPRO codes arbitrarily placed on the ground, with the coordinate axes +X in the general pointing direction of forward to aft of the vehicle, +Y from the driver side toward the passenger side and +Z upward.

All numbers in the tables were rounded to two decimal places.

Vehicle Test Results for the two Olympus E-450 Cameras Vehicle Errors for Camera #9914 imagery using its Z-D calibration: Camera #9914

VX

VY

VZ

Discrepancy Vector

RMS Error (Inches)

0.04

0.05

0.02

0.07

Error Range (inches)

-0.01 – 0.04

-0.00 – 0.02

-0.02 – 0.08

0.08

Vehicle Errors for Camera #9914 imagery using the Z-D calibration of camera #9896: Camera #9914

VX

VY

VZ

Discrepancy Vector

RMS Error (Inches)

0.04

0.04

0.32

0.07

Error Range (inches)

-0.02 – 0.11

-0.06 – 0.03

-0.07 – 0.06

0.06

Vehicle Errors for Camera #9914 imagery using EXIF recorded Focal Lengths: Camera #9914

VX

VY

VZ

Discrepancy Vector

RMS Error (Inches)

0.26

0.35

0.08

0.45

Error Range (inches)

-1.15 – 2.76

-0.49 – 0.63

-0.47 – 1.05

1.04

Vehicle Errors for Camera #9896 imagery using its Z-D calibration: Camera #9896

VX

VY

VZ

Discrepancy Vector

RMS Error (Inches)

0.06

0.01

0.02

0.06

Error Range (inches)

-0.12 – 0.09

-0.02 – 0.03

-0.03 – 0.06

0.04

Vehicle Errors for Camera #9896 imagery using the Z-D calibration of camera #9914: Camera #9896

VX

VY

VZ

Discrepancy Vector

RMS Error (Inches)

0.07

0.017

0.02

0.07

Error Range (inches)

-0.11 – 0.15

-0.03 – 0.04

-0.05 – 0.03

0.04

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Vehicle Errors for Camera #9896 imagery using EXIF recorded Focal Lengths: Camera #9896

VX

VY

VZ

Discrepancy Vector

RMS Error (Inches)

0.39

0.22

0.07

0.46

Error Range (inches)

-1.00 – .75

-0.57 – 0.73

-0.04 – .73

0.76

Vehicle Errors for Camera AFI imagery using the Z-D calibration of camera DCS: Camera AFI

VX

VY

VZ

Discrepancy Vector

RMS Error (Inches)

0.085

0.18

0.05

0.21

Error Range (inches)

-0.67 – 0.37

-0.06 – 0.06

-0.33 – 0.15

0.34

Vehicle Test Results for the two Kodak C142 Easyshare cameras

Vehicle Errors for Camera AFI imagery using EXIF focal length only:

Vehicle Errors for Camera DCS imagery using its Z-D calibration:

Camera DCS

VX

VY

VZ

Discrepancy Vector

RMS Error (Inches)

0.14

0.09

0.02

0.16

-0.36 – 0.88

-0.19 – 0.19

-0.15 – .034

0.33

Camera DCS

VX

VY

VZ

Discrepancy Vector

RMS Error (Inches)

0.03

0.03

0.02

0.05

Error Range (inches)

Error Range (inches)

-0.07 – 0.17

-0.04 – 0.05

-0.03 – 0.09

0.05

Vehicle Test Results for the Nikon S510

Vehicle Errors for Camera DCS imagery using the Z-D calibration of camera AFI:

Vehicle Errors for Camera Nikon S510 Coolpix imagery using its Z-D calibration:

Camera DCS

VX

VY

VZ

Discrepancy Vector

Camera DCS

VX

VY

VZ

Discrepancy Vector

RMS Error (Inches)

0.085

0.18

0.05

0.21

RMS Error (Inches)

0.84

0.08

0.27

0.12

Error Range (inches)

-0.76 – 1.75

-0.08 – 0.29

-0.31 – 0.66

0.64

Error Range (inches)

-0.24 – 0.60

-0.05 – .08

-0.08 – 0.13

0.21

Vehicle Errors for Camera DCS imagery using EXIF focal length only:

Vehicle Errors for Camera Nikon S510 Coolpix imagery using EXIF focal length only:

Camera DCS

VX

VY

VZ

Discrepancy Vector

Camera DCS

VX

VY

VZ

Discrepancy Vector

RMS Error (Inches)

0.27

0.28

0.07

0.40

RMS Error (Inches)

0.52

0.52

0.29

0.79

Error Range (inches)

-0.98 – 2.34

-0.14 – 0.40

-0.37 – 0.94

0.91

Error Range (inches)

-3.2 – 1.4

-0.6 – 0.37

-1.2 – 0.59

1.22

Vehicle Errors for Camera DCS imagery using FOOM: Camera DCS

VX

VY

VZ

Discrepancy Vector

RMS Error (Inches)

0.11

0.07

0.02

0.13

Error Range (inches)

-0.13 – 0.14

-0.13 – 0.13

-0.05 – 0.04

0.07

Vehicle Test Results for the Canon SD 1300IS NOTE: the Canon camera had “in-camera lens distortion correction”. The Linear Z-D mode was required for the Canon SD 1300 IS. All other cameras in the study used the Power-ZD mode. The correct Z-D mode was determined automatically by iWitnessPRO.

Vehicle Errors for Camera AFI imagery using its Z-D calibration: Camera AFI

VX

VY

VZ

Discrepancy Vector

RMS Error (Inches)

0.06

0.09

0.02

0.1

Error Range (inches)

-0.22 – 0.52

-0.05 – 0.08

-0.09 – 0.21

0.2

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Vehicle Errors for Camera Canon SD1300 IS imagery using its Z-D calibration: Camera Canon

VX

VY

VZ

Discrepancy Vector

RMS Error (Inches)

0.09

0.08

0.02

0.12

Error Range (inches)

-0.23 – 0.53

-0.03 – 0.06

-0.1 – 0.21

0.20

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Vehicle Errors for Camera Canon SD1300 IS imagery using EXIF focal length only: Camera Canon

VX

VY

VZ

Discrepancy Vector

RMS Error (Inches)

0.33

0.11

0.16

0.38

Error Range (inches)

-5.34 – 2.13

-1.32 – 1.57

-2.09 – 0.86

2.12

R

esults of Study The tests of the two Olympus E-450 DSLRs showed the Z-D based networks matched the control network better than 0.1” RMS. Similarly, the two networks which used the Z-D calibrations from the other camera, matched the control network of the Olympus E-420 better than 0.1” RMS , which suggests that using the Z-D calibration from exemplar DSLR cameras might not adversely affect small scale or vehicle crush reconstruction analysis The maximum errors for Z-D based networks for the DSLR cameras were less than 0.2 inches.

The tests of the two Olympus E-450 DSLRs EXIF based networks (using only the approximate focal length for the camera parameters) were significantly less accurate and produced RMS errors six or more times larger than the Z-D calibration networks. The largest EXIF based network errors for the two cameras ranged from about 0.76 inches to 1.04 inches. While the use of an EXIF focal length based network might seem to be acceptable in some small scale situations, there is insufficient empirical or theoretical bases to support that application, and it is not recommended.

The tests of the two Kodak C-142 PAS cameras showed the Z-D based networks also matched the control network within 0.1” RMS. The Kodak Z-D RMS error was a bit larger than the DSLR Z-D RMS error and showed considerable variation between the individual Kodak cameras, but was impressive for an inexpensive camera, when its Z-D calibration was used. The maximum absolute errors for Z-D based networks for the Kodak cameras were less than 0.7 inches, which is small compared to the uncertainty of other variables in a vehicle crush analysis.

The accuracy of two Kodak networks which used the Z-D calibrations from the other Kodak camera, were comparable to the Kodak EXIF based networks, which do not have an empirical or theoretical basis, so neither exemplar Z-D or EXIF based networks are recommended for PAS cameras.

The tests of the two Kodak C-142 PAS, EXIF based networks (using only the approximate focal length for the camera parameters) were significantly less accurate and up to 16 times larger in the discrepancy error range than their Z-D calibration networks.

The test of one Kodak C-142 network, treated as an unknown camera with focal lengths and lens distortion parameters determined by the iWitnessPRO FOOM method, produced errors comparable to the Z-D calibration network for the same camera. The test demonstrates the capability of the FOOM, but it requires significantly more 3D knowledge within the image and greater effort.

based network errors were several times larger than the Kodak EXIF network errors.

The tests of the Canon SD 1300 IS PAS camera showed the Z-D based network accuracy was comparable to the Kodak C-142 PAS camera Z-D networks. However, the Canon EXIF based network errors were as much as 6 times larger than the Kodak EXIF network errors. The Canon imagery had in-camera correction for lens distortion so the Z-D calibration was linear rather than a power function.

It has been demonstrated by the camera parameters used, and resulting data presented in the Vehicle Test Result Tables, that significantly larger errors for the EXIF based network occurred when the principal point and K1 radial distortion are “defaulted” to zero (0) for the camera’s inner orientation parameters, and the fact that the EXIF focal length is only ‘approximate’ rather than an accurate metric calibration of these same parameters using Z-D.

C

onclusions and Recommendations Zoom-Dependent Camera Calibration provides a method to efficiently and reliably obtain 3-dimensional measurements from consumer grade DSLR and PAS digital camera images, without restricting the full use of a zoom lens capability. The accuracy of Z-D networks has been demonstrated to be suitable for accident reconstruction analysis projects.

Obtaining a Z-D calibration for a camera involves a reasonable initial effort and negligible additional processing effort for subsequent networks, in return for removal of the traditional ‘fixed’ zoom lens restriction in close-range photogrammetry.

Network analysis based on Z-D calibration has a provable basis to be a valuable tool for image-based measurement in accident reconstruction applications.

The tests support Z-D as a much more efficient, but equally accurate, alternative (or an additional method available) to the more traditional photogrammetrical means requiring control points, e.g. FOOM. The accuracy of a Z-D based network was comparable to a FOOM based network while the EXIF based networks in this study were much less accurate. Z-D calibration of the imagery camera provides an empirical basis for confidence in the accuracy of a Z-D based network, while there is no equivalent support for an EXIF based network and its use is not recommended because it is unpredictable.

Radial distortion is present in varying degrees in consumer grade digital cameras but its magnitude is not identified in readily available camera specifications. The importance of determining the radial distortion and correcting the network to account for that distortion had been demonstrated by others, along with corrective schemes. A Z-D calibrated camera determines and corrects for the radial distortion, focal length and principal point offsets automatically throughout the full zoom range of a digital camera’s telephoto lens.

The small scale tests of the Nikon S510 PAS camera showed the Z-D based network accuracy was comparable to the Kodak C-142 PAS camera Z-D networks. However, the Nikon EXIF

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Collision Magazine 77

The Use of EDR Data in Vehicle Accident Reconstructions Raymond M. Brach, PhD, PE University of Notre Dame Brach Engineering, LLC

bstract This article describes two example crash reconstructions intended to be representative of vehicle accident reconstructions combining Event Data Recorder (EDR) data with other quantitative physical evidence. Underreporting of the speed values in EDR data is known to occur. Its cause is examined and a way to correct the speeds for heavy braking is presented. Analysis of EDR speed versus time data to estimate vehicle acceleration and position is also examined. The first example is a vehicle-pedestrian collision for which the vehicle EDR data includes precrash speeds. The second example is a reconstruction of a head-on crash of two vehicles where EDR data include both precrash speeds and delta-V values. In this example, a single comprehensive reconstruction of the initial vehicle speeds is carried out combining the EDR data

A

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with a crush energy analysis. The reconstruction is formulated in a manner such that the results satisfy the principle of impulse and momentum. ccident Reconstruction Vehicle accident reconstruction is a process carried out with the specific purpose of estimating, in both a qualitative and quantitative manner, how an accident occurred. This process is accomplished using engineering, scientific and mathematical principles/laws and is based on physical evidence obtained through an accident investigation. The collection of facts, data and physical evidence associated with the circumstances of an accident is referred to as accident investigation.

Determining what happened in an accident and how it happened is referred to as accident reconstruction.

A

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Using EDR1 Data in a Vehicle Accident Reconstruction: In a recent article [2], the author presents a detailed discussion of meanings, interpretations and content of the term accident reconstruction, such as above. The terms “complete reconstruction” and “situational complete reconstruction” are introduced and explored. In particular, the question of whether or not Event Data Recorder (EDR) data is accurate and reliable and if and how it should be used in an accident reconstruction is addressed. Assuming that in a particular crash the data imaged from a EDR is determined to be reasonably accurate and reliable, the answer is, of course such data should be used. When other reliable quantitative data (such as skid mark lengths, crush energy calculations, etc.) for a particu-

lar crash are available, all should be collectively used in the reconstruction process. Methods outlining the direct use of EDR data in the reconstruction of collisions have been discussed, documented and used for years, especially ΔV values [3, 4, 5, 6, 7]. As used in the examples in References 5, 6 and 7, the longitudinal component of a vehicle’s ΔV in a crash can be incorporated into a reconstruction using appropriate impact models such as the planar impact equations (impact equations that take vehicle rotational velocities into account). More vehicles are now equipped with multi-axis accelerometers and so longitudinal, lateral and rotational ΔV values are becoming available for inclusion in reconstructions. EDR data can and should be used to carry out reconstructions.

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Collision Magazine 79

“” Data imaged from an EDR other than the value of a vehicle’s Delta-V is very useful.

Data imaged from an EDR other than the value of a vehicle’s ΔV is very useful. Moreover, additional processing of the EDR data can often provide vital reconstruction information. For example, preimpact vehicle speeds are often recorded by a EDR. Through the use of numerical integration, speed-time data can reveal the preimpact displacement of the vehicle as a function of time (relative to the vehicle position at Algorithm Enable, AE). Estimates of levels of deceleration can be obtained from changes in preimpact speed over time. Examples are presented here of two reconstructions that use EDR data in combination with other accident data and physical evidence in such a way.

The first is a vehicle-pedestrian collision and the second is a head-on crash of two vehicles. Both are hypothetical, but the second is based on a staged collision with actual data [2], from known, measured results. In general, each accident and its reconstruction are unique. The two examples presented here are just that, examples. However the approach of using all available quantitative data, traditional and from EDRs, in a scientific and mathematical manner is illustrative of what is happening in the field of accident reconstruction.

heel Slip and Underreporting of Precrash Speeds

by EDRs Before proceeding to Example 1, it is helpful to discuss the concept of wheel slip that occurs during braking. Braking affects the rotational speed of a vehicle’s wheels through application of a resistive torque to each wheel. This torque causes the wheel to have a rotational speed (angular velocity) slower than a freely rolling wheel, to the extent that a locked wheel has zero rotational speed even as a vehicle is still moving forward (skidding). That is, the vehicle has a forward speed, but a speedometer connected to a vehicle speed sensor monitoring the mechanical powertrain output would read zero.

The presence of wheel slip during braking can cause the speed indicating device on a vehicle to provide a speed value lower than that of the speed of the vehicle relative to the ground, that is, underreport the speed. Although the speed measuring device can vary from vehicle to vehicle (transmission shaft output, wheel sprocket speed, etc.), EDRs report the speed indicated by the vehicle’s speed measuring device, or sensor(s).

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Figure 1: Velocities of a rotating wheel with slip.

Figure 1 shows a rolling wheel with a center velocity, V (the speed of the vehicle), a wheel rotational angular velocity, ω, the tire/wheel velocity at the contact point with the pavement, VP, and a rolling radius, R. Braking wheel slip, s, typically is defined as [3]:

(1) Note that for a locked wheel, ω = 0, and the slip s = 1; for pure, or free, rolling, V = Rω and the slip s = 0. All conditions of braking are controlled by the brake pedal force which controls slip to range between 0 ≤ s ≤ 1. Typically, antilock braking systems (ABS) control wheel slip to cycle over a region of maximum tire force [3, 8]. This means that the slip is cycled to remain typically in the range of 0.15 ≤ s ≤ 0.25. Let the Rω term in Equation 1 represent an equivalent output of a speed sensor (speedometer signal) that is recorded and stored by the EDR as the vehicle speed such that Rω = VEDR. Solving for the speed of the vehicle indicated by the EDR, VEDR, from Equation 1 gives:

(2) It is clear from Equation 2 that when a brake is applied causing s to be greater than zero that the reported speed (as indicated by the EDR) is less than the vehicle speed. For example, if the vehicle speed at a given precrash time is V = 30 mph (44 ft/s, 48.2 kph) but is indicated as VEDR = 25 mph (36.7 ft/s, 40.2 kph), this would imply a wheel slip (averaged over the vehicle’s four wheels) of s = 0.17, an underreporting of 5 mph (7.3 ft/s, 8.0 kph), or 17%. Reust and Morgan [15] found from their tests that speeds during braking can be underreported by Sensing and Diagnostic Modules (SDMs) by 8% to 18% and significantly more at low vehicle speeds. With an understanding of wheel slip, it is possible to estimate speed of the vehicle more accurately if the average slip of the vehicle’s wheels is known or can be reasonably estimated. In the following example, the accelerations suggested by the EDR data are estimated using the information that the vehicle’s ABS system is in operation.

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xample 1 Vehicle-Pedestrian Collision: This is an example where a pedestrian, a young man weighing 150 lb, is hit by a 4000 lb pickup truck with a high vertical front profile. This is typically referred to as a forward projection pedestrian collision [3], where the pedestrian is propelled straight forward from the vehicle (as compared to being wrapped onto the hood and interacting with the windshield). Figure 2 shows some of the conditions of the accident including the rest positions of the vehicle and pedestrian. It was not possible to determine the point of impact from the scene evidence but it was determined from the rest positions that the pickup truck came to a stop 4 feet closer to the point of impact than the pedestrian. In this case, the impact severity did not reach a level sufficient to actuate the driver’s airbag, but the event was recorded by the EDR as a Non-Deployment event. The road conditions were dry and it is known that the vehicle had an ABS which was actuated continuously over a distance of at least 60 feet before coming to rest.

E

Table 1 shows the precrash data imaged from the EDR. The data have been examined and found to be reliable with no limitations indicated. Table 2 shows the values of the vehicle’s average acceleration calculated from the changes in the speed values shown in Table 1. The acceleration value of -1.23 g’s at t = -1 seconds before Algorithm Enable (AE) indicates a high level of braking consistent with the observation of ABS activation. However, with ABS activation, wheel slip would cause the speed of 42 mph (61.6 ft/s, 67.5 kph) at t = -1 s before AE to be underreported. Using an average wheel slip of s = 0.2, this means that the vehicle speed at t = -1 s before AE is 42/0.8 = 52 mph, truncated (76.3 ft/s, 83.6 kph). In turn, this implies that the actual acceleration from 69 mph (101.2 ft/s, 110.9 kph) to 52 mph (76.3 ft/s, 83.6 kph) is -0.77 g’s, not -1.23 g’s. If it is assumed that braking in the last second before AE remains at this level, the speed at AE can be estimated and is 35 mph (51.3 ft/s, 56.3 kph). These corrected and extrapolated data are shown in Tables 3 and 4. If AE occurred at the time of impact with the pedestrian, then the vehicle speed at impact was 35 mph. This information can be evaluated using a vehiclepedestrian impact model.

Seconds before AE

Vehicle Speed (mph)

Engine Speed (rpm)

Percent Throttle

Brake Switch

-5

69

3048

85

Off

-4

71

3048

85

Off

-3

71

2056

71

On

-2

69

1208

6

On

-1

42

980

0

On

Table 1: Data from the CDR Report for the Vehicle Striking the Pedestrian in Example 1 Average Acceleration g’s .09 .00 -.09 -1.23 Table 2: Average Accelerations, Computed from Speed in Column 2 of Table 1

Figure 2: Vehicle-pedestrian accident diagram.

Seconds Before AE

Vehicle Speed (mph)

Engine Speed (rpm)

Percent Throttle

Brake Switch

-5

69

3048

85

Off

-4

71

3048

85

Off

-3

71

2056

71

On

-2

69

1208

6

On

-1

52

980

0

On

0

35

On

Table 3: Data from the CDR Report for the Vehicle Striking the Pedestrian in Example 1, Corrected for Underreporting of Vehicle Speed, s = 0.20

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Collision Magazine 81

Average Accelerations g’s 0.09 0.00 -0.09 -0.77 -0.77 Table 4: Average Accelerations, Computed from Speeds in Column 2 of Table 3 An appropriate vehicle-pedestrian impact model [3, 14] exists that relates the rest positions of the vehicle and the pedestrian and allows a full analysis of the collision using the available information. In summary, the impact speed was 35 mph (51.3 ft/s, 56.3 kph), the difference between the rest positions is known to be 4 feet and the deceleration of the vehicle from impact to rest was 0.77 g’s. Other collision parameters are also known. For example, the vehicle and pedestrian weights (and masses) are known. For a forward projection collision, the pedestrian launch angle is zero (the center of mass of the pedestrian is propelled forward horizontally) and the wrap distance is zero. One of the unknowns however is the value of the equivalent drag factor of the pedestrian along the ground.

It is known generally to lie in the range 0.7 ≤ fp ≤ 0.8 [3]. The approach taken here is to put all of the known information (including the EDR speed of 35 mph) into the vehicle-pedestrian model and determine the corresponding value of fp. That is, for a vehicle impact velocity of 35 mph and a rest position separation distance of 4 feet, the value of fp is found and compared to the feasible region.

Figure 3 (on the next page) is a copy of the vehicle-pedestrian impact spreadsheet from the VCRware software package [9].

Using the spreadsheet’s Goal Seek feature, it is found that a value of fp = 0.74 is required for agreement with all of the other collision conditions. (Note that the separation distance is negative 4 feet because of the definition of positive displacement in the model.) Since fp lies in the feasible range, the reconstruction satisfies all conditions of the scene observations and the speed values from the corrected EDR data. Overall the reconstruction has not only determined the speed of the vehicle at impact but (from Fig 3) the pedestrian throw distance, sp, is now known to be 53.4 feet — locating the unknown point of impact. In addition, the impact of the pedestrian with the ground was approximately 20.5 feet from the point of initial contact, and so on.

A reconstruction as carried out above, but using the uncorrected deceleration of the vehicle at AE (-1.23 g’s) and the uncorrected speed at AE (15 mph) yields a frictional drag value of the pedestrian of fp = 1.0, which is contrary to experimental data.

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A check can be made on the above vehicle-pedestrian collision results by making a comparison with other models. For a throw distance of sp = 53.4 ft (16.3 m), the experimental forwardprojection model of Happer, et al. [10], gives a vehicle speed at impact, vc0, in the range of 22 mph (32.3 ft/s, 35.3 kph) to 35 mph (51.3 ft/s, 56.3 kph). For a throw distance of sp = 53.4 ft (16.3 m), the forward projection model of Wood [11], gives a vehicle speed, vc0 in the range of 18 mph (26.4 ft/s, 28.9 kph) to 35 mph (51.3 ft/s, 56.3 kph). The above reconstructed speed of 35 mph lies within the ranges of both models, although at the high end. Note that this reconstruction process may not apply to all vehicle-pedestrian collisions and can vary with different conditions and data.

One additional part of the reconstruction from the EDR data remains to be done. Since velocity is the mathematical derivative of the position, the position (or displacement) is the mathematical integral of the velocity. Figure 4 shows the displacement of the pickup truck as a function of time before AE found by numerical integration of the (corrected) speed data in Table 3. It shows, for example, that in the last two seconds before the impact, the truck traveled approximately 150 feet.

Finally, the above model of vehicle-pedestrian collisions has been validated [3, 14] and is one of the few models that can be used to reconstruct a vehicle-pedestrian collision using the difference in rest positions of the vehicle and pedestrian [13, 16] xample 2: Head-On Crash of Two Cars: In the article on the use of EDR data and complete reconstructions [2], conditions are presented corresponding to a head-on collision.2 A reconstruction of this crash is done here. The crash is based on a staged headon crash of a 2009 Chevrolet Impala (Vehicle A) and a 2008 Ford Focus (Vehicle B). Because the crash is a head-on central collision (i.e., preimpact and postimpact rotational velocities of the vehicles are negligible), point mass, impulse and momentum theory [3] can be used. Among the data available for the reconstruction of the collision are those imaged from the EDR of both vehicles. These contain the speed of the Focus in the five seconds up to t = 0 s before impact and the speed of the Impala including t = -0.5 s before AE. In summary:

E

Figure 4: Vehicle speed and displacement using corrected EDR data (Table 3).

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Figure 3: Spreadsheet showing the reconstruction of the vehicle-pedestrian impact, Example 1. Shaded cells are input values for an analysis but unknown input values can be found using the ‘What If ’ feature of the spreadsheet for a reconstruction when output information is known. www.collisionpublishing.com

Collision Magazine 83

•

The Focus data show no preimpact brake lamp actuation with the speed at t = 0 s as 25.9 mph (37.99 ft/s, 41.7 kph).

The Impala data show brake lamp actuation beginning at t = -0.5 s before AE and a speed at t = -0.5 s of 23 mph (33.73 ft/s, 37.0 kph).

The EDR data include the longitudinal crash ΔV values, ΔV = 19.24 mph (28.2 ft/s, 30.9 kph) for the Impala and ΔV = 23.15 mph (34.0 ft/s, 37.2 kph) for the Focus.

• •

The frontal residual crush of both vehicles was measured and crush energy analyses were carried out [2]. The results of these analyses are expressed as values of ΔVC, computed from crush energy: • •

ΔVCA = 18.2 mph (26.7 ft/s, 29.3 kph) for the Impala ΔVCA = 23.3 mph (34.2 ft/s, 37.5 kph) for the Focus.

The initial speeds of each vehicle cannot be reconstructed using the results of the crush energy analysis alone; only the closing speed can be determined. Moreover, EDR data is known to contain inaccuracies and that values sometimes are truncated.

However, if the EDR data are available and are considered reliable, a reconstruction of the preimpact speeds of the vehicles can be carried out using combined data from the crush analysis and the EDR. This minimizes the effects of inaccuracies and truncation errors and allows a reconstruction rather than comparison of the individual values of ΔV from the EDR with their corresponding values from the crush analysis and separately using the speeds at AE from the EDR data.

A convenient way to carry out such a reconstruction is to place the impulse-momentum model equations into a spreadsheet [3], set up the computation of Q and let the optimization routine of the spreadsheet carry out the minimization [12]. Figure 5 shows a spreadsheet from the VCRware software package [9] that is programmed to handle central impacts (including low speed impacts) using the impulse-momentum model. The equations in this spreadsheet allow the effects of braking-tire impulses to be taken into account because for low speed collisions such effects can be significant.

Figure 5 (on the following page) shows the results of the minimization process. Figure 6 shows the input to the spreadsheet’s optimization routine (called “Solver”), including the “target” cell containing Q which is to be minimized, and the cell numbers of the quantities whose values are to be determined (reconstructed) through the minimization process. The reconstructed values of the initial speeds are: VA = -20.52 mph (30.1 ft/s, 33.0 kph) and VB = 23.42 mph (34.4 ft/s, 37.7 kph). Because the spreadsheet solves the general central impact problem many other reconstructed results are shown. Table 6 shows a summary of results of the speed reconstruction. Table 6 also contains the initial speeds measured from the crash test for comparison.

Method of Least Squares: An analysis of a combination of the crush and EDR data can be carried out using the method of least squares, described as follows. The quantity Q is defined as the sum of squares of differences between each value of a variable obtained from physical evidence (e.g. the ΔV from the EDR data) and the value of that same variable that corresponds to the solution of an appropriate physical model (here the point mass central impact equations). Let:

Figure 6: Input to Solver routine for minimization of Q (cell C40) in order to find the vehicle initial speeds (cells C14 and C15).

(3) where n is the number of variables whose values are to be used from the data, wi is a weighting factor, uidata is the value of variable i from physical evidence and ui is the corresponding value of variable i that satisfies the physical model. The approach is to minimize Q in a way that determines the values of variables, vi from the model of the physical system, that are needed from a reconstruction. This process satisfies the physical model AND matches the physical evidence in a “best, or optimal” way. It is not always necessary that the reconstructed/unknown variables, vi be the same as the fitted variables, ui, although they can be. In this example the values used from the data are the four values given in Table 5. The variables to be found (reconstructed) are the initial speeds, VA and VB. All values of the weighting factors, wi, were chosen to be unity, that is, wi = 1, i = 1, . . ., 4.

Impala (Veh A)

Focus (Veh B)

ΔV from crush, mph

18.2

23.3

Initial Velocity, EDR, mph

23.0

25.9

Table 5: Physical Data used for Least-Squares Reconstruction

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Collision Magazine

Impala (Veh A)

Focus (Veh B)

Reconstructed Initial Speed, mph

20.5

23.4

Reconstructed Velocity Change, mph

20.43

23.52

Measured Initial Test Speed, mph

22

25

Table 6: Reconstruction and Test Results Note that the reconstructed closing velocity that satisfies the impulse momentum equations is VC = 43.9 mph (64.4 ft/s, 70.7 kph).

Some comments can be made concerning the reconstruction process (least-square minimization) and results.

•

The Impala EDR showed a brake application in the last half-second before AE. Depending on the level of braking, this could have added an external frictional impulse to the collision. This impulse could have been taken into account in the least square minimization process by adding the friction coefficient, fA (see Figure 5), of Veh A to the list of unknowns to be found. This was done initially, but the closing speed of the collision was high enough to be considered a high speed collision and the change in results due

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Figure 5: Spreadsheet showing the results of the least-square reconstruction, Example 2. Shaded cells are input values for an analysis but unknown values can be found using the ‘What If ’ feature of the spreadsheet for a reconstruction when output information is known. www.collisionpublishing.com

Collision Magazine 85

to the external friction impulse, if it existed, was negligible.

eferences 1. NHTSA: 49 CFR Part 563 - Event Data Recorders.

R

•

The coefficient of restitution was chosen to be fixed at e = 0 for the least-square reconstruction. It too could have been found as part of the least-square process. Initially it was included in the least-square minimization, was found to be zero and was then simply fixed at e = 0.

2. Haight, W. R. “Rusty”, “Using CDR System Data in Crash Reconstruction or What does the Term ‘Complete Reconstruction’ Mean?”, Collision, Volume 6, Issue 1.

•

A question could be asked as to why the ΔV values from crush were used in the fitting process rather than the ΔV values from the EDR. This was done intentionally because the values generated from the crush energy analyses were considered to be independent from the EDR data. Because the impact speeds from the EDR were being used, the use of crush energy data gives a more balanced reconstruction.

4. Schmidt, Bruno, “Two-Dimensional Analysis of EDR Information”, Collision, Volume 2, Issue 1, 2007.

ummary and Conclusions Example 1 shows that EDR data and other, traditional, quantitative accident data can be combined to provide a reasonably accurate reconstruction. It also shows how knowledge of wheel slip can be used to correct underreported EDR vehicle speeds during braking. It shows that the location of the vehicle-pedestrian impact (point of impact), or throw distance, is not always needed to reconstruct the vehicle speed. Note that few pedestrian throw models allow such reconstructions; a comprehensive study [16] mentions none.

S

3. Brach, Raymond and Matthew Brach, Vehicle Accident Analysis and Reconstruction Methods, SAE International, 1st Ed, 2005, 2nd Ed, 2011.

5. Brach, Raymond M. and R. Matthew Brach, “Vehicle Accident Reconstruction Methods”, SAE Professional Development Seminar, 2004-2010, SAE International, Troy, MI. 6. Brach, Raymond M. and R. Matthew Brach, “Analysis of Collisions, Point Mass Mechanics and Planar Impact Mechanics”, Collision, Volume 2, Issue 1, 2007.

“” the method of least squares used above reconstructs the initial vehicle speeds (and closing speed) using combined crush data and EDR data.

10. Happer, A., Araszewski, M., Toor, A., Overgaard, R., and Johal, R., "Comprehensive Analysis Method for Vehicle/Pedestrian Collision", Paper 2000-10-0846, SAE, Warrendale, PA, 2000.

11. Wood, D. P. and D. G. Walsh, "Pedestrian Forward Projection Impact" IJCrash, Vol 7, No 3, Woodhead Publishing, UK, 2002.

12. Hallberg, B., S. Kinkoph, B. Ray, et al., Special Edition Using Microsoft Excel 97, Que Corp, 1997.

13. Evans, A. K. and R. Smith, “Vehicle speed calculation from pedestrian throw distance”, IMechE, Proc Instn Mech Engrs, Vol 213, Prt D, 1999.

14. Davis, Gary, “A Baysian Approach to Cross-Validation in Pedestrian Accident Reconstruction”, Paper 2011-01-0290, SAE International, 2011.

In general, both examples show that the use of appropriate, validated mathematical models used with conveniently formulated software allows an accurate reconstruction to be carried out using data from numerous sources.

Collision Magazine

8. Bosch Automotive Handbook, 7th Ed., Robert Bosch GmbH, Stuttgart Germany, 2007.

9. VCRware, Brach Engineering, Granger, IN 46530, www. brachengineering.com.

From Example 2 the method of least squares used above reconstructs the initial vehicle speeds (and closing speed) using combined crush data and EDR data. The results are reasonably accurate in that the reconstructed initial speeds of the vehicles are within approximately 1.5 mph (2.4 kph) of the measured test values and also that the reconstructed collision closing speed of 44 mph (64.5 ft/s, 70.7 kph) is within 3 mph (4.8 kph) of the measured value, 47 mph (68.9 ft/s, 75.5 kph). A significant feature of this procedure is that all of the reconstructed results satisfy the central impact equations of Newton’s laws.

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7. Brach, Raymond and Matthew Brach, "Analysis of Collisions, Point Mass Mechanics and Planar Impact Mechanics", Collision, Volume 2, Issue 2, Page 15, 2007.

15. Reust, T. J. and J. M. Morgan, “Detailed Comparison of Vehicle Speed and the Speed Recorded by an SDM”, Collision, Volume 2, Issue 2, Fall, 2007.

16. Bonnett, G. M., “Pedestrian Vaults, Humans Going Ballistic”, Institute of Police Technology and Management, FL, 2005.

Footnotes: 1. The terms Event Data Recorder (EDR) and Crash Data Recorder (CDR) are often used synonymously. EDR is used in this paper since it conforms to terminology of the NHTSA (National Highway Traffic Safety Administration), Ref 1 [1].

2. The reader is encouraged to refer to [2] for additional information of the crash conditions and limitations of the EDR data, particularly for Example 2.

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Fundamentals of Highway and Roadside Design for the Accident Reconstruction Specialist Francisco R. Klein, PE, MECE Klein Engineering, PSC.

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I

ntroduction Accident reconstruction specialists focus mostly on elements of the scene of an accident when determining its causes. This article presents some of the fundamental elements of highway and roadside design as an essential part of the investigation of any accident, because there are factors pertaining to the site of an accident that may prove to be determining when evaluating its reconstruction.

The focus of this article will be on highway and roadside design guidelines used in the United States and developed by the American Association of State Highway and Transportation Officials (AASHTO).

B

ackground Transportation engineering is a relatively young specialty when compared to other engineering disciplines. People have always had the need to move/travel across long distances for the purposes of social expansion, commerce, or leisure; however, transportation, as a dedicated engineering discipline, is slightly over 100 years old.

Roads have existed since early in human history. They have served conquerors from different ages and geographical locations to mobilize their armies and wage wars to expand their domains-- thus, the well-known phrase, “all roads lead to Rome”. Roads have always been an integral part of cities throughout the world, providing a public space for the mobilization of people and goods.

Traffic engineering became increasingly complex with the introduction of the private automobile. As cities continued to grow with an ever-increasing amount of automobiles sharing roads with pedestrians and other modes of transportation, the need for adequate traffic management techniques became more relevant than ever before in history.

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Collision Magazine 89

In addition, private automobiles gave individuals newfound freedom to travel independently and comfortably, not only within cities, but also between cities and rural areas. A system of roadways had to be constructed in order to provide the necessary infrastructure to accommodate motor vehicle traveling.

After World War II (WWII), president Dwight D. Eisenhower set the goal of building a national strategic highway network to provide for the efficient transportation of goods and military personnel in the event of a national emergency. Extensive research was carried out in order to develop design guidelines and have standardized design parameters in the construction of highways across the nation. The focus of these guidelines was on providing safety, comfort, and efficiency to drivers.

Highway and roadside design has continuously been evolving since the 1960’s, when the U.S. government began the construction of the interstate highway system and most of the national roadway network. The different agencies and organizations in charge of developing regulations and design guidelines throughout the years have consistently focused on the ultimate goal of providing users with safe and efficient roadways to travel on.

By the late 1960’s and early 1970’s, agencies had gathered and analyzed enough data on highway accidents, which allowed them to conclude that vehicle travel safety was not only limited to providing a safe highway design, but also required a safe roadside environment be provided in order to reduce fatalities and serious injuries of occupants involved in run-off-the-road accidents.

Providing a safe roadside is, therefore, an integral part of highway design now-a-days. Design guidelines provide for ideal roadside conditions, as well as for the installation of adequate safety appurtenances in such locations where geographical, topographical, and other constraints do not allow ideal conditions to be constructed.

complete functional design system provides a series of distinct travel movements which, in most cases, include a main movement, transition, distribution, collection, and access or termination.

Determining the design speed of a highway is another fundamental element during the design process. According to AASHTO, “It should be evident that there are important differences between the design criteria applicable to low- and high-speed designs. Because of these distinct differences, the upper limit for low-speed design is 45 mph, and the lower limit for high-speed design is 50 mph.”

Therefore, when evaluating the site of an accident, it is critical to determine whether the highway on which it occurred is a high- or low-speed facility. This determination will be of significant importance for the accident reconstruction specialist when evaluating the principal design aspects of the highway under study.

According to AASHTO [1], “The assumed design speed should be a logical one with respect to the topography, anticipated operating speed, the adjacent land use, and the functional classification of the highway. Except for local streets, where speed controls are frequently included intentionally, every effort should be made to use as high a design speed as practical to attain a desired degree of safety, mobility, and efficiency within the constraints of environmental quality, economics, aesthetics, and social or political impact.”

The design speed is a decisive design element both for the horizontal (plan view) and vertical (section) alignment of a roadway. The selected design speed is the fundamental variable used in the determination of the minimum horizontal curve radius of a highway, as observed in the equation presented by AASHTO in Figure 1, and it serves as an overall design control.

The fundamental design elements to be discussed in this article are those presented in AASHTO’s A Policy on Geometric Design of Highways and Streets, 2004 Edition and Roadside Design Guide, 3rd Edition. Other available design manuals and guidelines, such as FHWA’s Manual on Uniform Traffic Control Devices and its recently introduced Highway Safety Manual, provide additional valuable insights into highway safety.

A

Policy On Geometric Design Of Highways And Streets, AASHTO, 2004 [1] AASHTO’s A Policy on Geometric Design of Highways and Streets, 2004 (“Green Book”) is an engineering best practices guide for the design of highways in the United States.

However, the Green Book has been adopted by many countries around the world for the same purpose.

Highway classification is the first discussion presented in the Green Book. The determination of an appropriate functional classification of a highway is a key element when defining the elements that will control its design. There are significant differences in the needs and requirements of drivers using rural and urban roads. Within urban and rural roadways, there are also important differences between those that primarily satisfy mobility requirements and those that address access needs.

Major highway systems, whether urban or rural, satisfy the need of mobility of travelers. Likewise, the minor highway systems focus more on providing accessibility to its users. A 90

Collision Magazine

Figure 1: AASHTO’s Equation for Minimum Horizontal Curve Radius (Source: AASHTO) The minimum horizontal curve radius presented above depends on the following variables: • • •

Design speed, V, in mph or kph Maximum superelevation rate, fmax Maximum side friction factor, emax

Superelevation rates are provided in horizontal curves as a means of offsetting the effect of the centripetal force acting on a vehicle by inclining the surface of the pavement, thus allowing the gravitational force to become part of the system of forces acting on the vehicle, helping it stay on its path while traversing a curve. According to the Federal Highway Admin-

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istration (FHWA) [5], “Superelevation is the rotation of the pavement on the approach to and through a horizontal curve.

Superelevation is intended to assist the driver by counteracting the lateral acceleration produced by tracking the curve.”

Maximum superelevation rates are expressed as a percentage of the slope to width ratio of the pavement’s cross-section and are controlled by four (4) factors: • • • •

Climate conditions Terrain Conditions Type of area Frequency of very slow-moving vehicles

As with any element of highway design, no maximum superelevation rate is universally applicable. However, rates higher than 8% are only used in places where ice and / or snow are not expected. The highest commonly used rate is 10%, and, although 12% may be accepted in particular cases, it is considered to be beyond practical limits.

When evaluating the site of an accident, the accident reconstruction specialist must not only evaluate whether the superelevation rate is appropriate, but also if the transition design controls are in compliance with design guidelines. Whereas it is a traditional tangent-to-curve transition, or a spiral curve, it is important to analyze whether appropriate tangent runout, superelevation runoff, and / or spiral length are adequate.

The side friction factor represents the vehicle’s need for side friction and the lateral acceleration acting on it as it travels through a horizontal curve. AASHTO recommends that this value should be conservative for dry pavements and should provide an ample margin of safety against skidding on pavements that are wet.

A roadway’s vertical alignment is equally important as its horizontal alignment due to its effects on drivers traveling through it. The vertical alignment of a highway is greatly determined by the topography of the area on which it is constructed. Terrain is usually classified by engineers as level, rolling, or mountainous.

Although a passenger car can generally negotiate grades as steep as 4% to 5% without an appreciable loss in speed, the effects of grade on trucks is much more pronounced. The design of a roadway’s vertical alignment should provide for the latter, since it has direct implications on the free-flow speed of vehicles traveling through a roadway and the expected levels of service to be experienced by users.

While changes in direction on the horizontal plane are achieved by the use of horizontal curves, changes in grades on the horizontal plane are solved by using vertical curves. Vertical curves are used when the arithmetic difference of the percentage of the tangent grades is greater than 0.5. There are two main classifications of vertical curves: crest and sag. The different types of vertical curves are presented in Figure 2.

Figure 2: Types of Vertical Curves (Source: AASHTO)

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Collision Magazine 91

ing distance. The former is the distance traversed by a vehicle during the driver’s reaction to an object on its path; the latter is the distance traversed by a vehicle once the driver has applied the brakes as a reaction to said object.

Per AASHTO [1], “Studies documented in the literature show that most drivers decelerate at a rate greater than 4.5 m/s² (14.8 ft/s²) when confronted with the need to stop for an unexpected object in the roadway. Approximately 90 percent of all drivers decelerate at rates greater than 3.4 m/s² (11.2 ft/ s²). Such decelerations are within the driver’s capability to stay within his or her lane and maintain steering control during the braking maneuver on wet surfaces. Therefore, 3.4 m/ s² (11.2 ft/s²) (a comfortable deceleration for most drivers) is recommended as the deceleration threshold for determining stopping sight distance.”

The equation presented by AASHTO to calculate a vehicle’s stopping sight distance is the following: d = 1.47*Vt + 1.075*V²/a (U.S. customary units) Where: • • •

Figure 3: Green Book’s Exhibit 3-70 (Source: AASHTO) The length of a vertical curve is not only determined by the two (2) tangent grades, but sight distance must also be considered , as presented in figures 3 and 4.

Another fundamental element in highway design is the stopping sight distance. This is a calculated distance used by designers to provide drivers with a distance that is enough to perceive an object on their path, judge if this object presents a hazard if impacted by the vehicle, and react so that the vehicle will stop before impact, thus avoiding a collision with that object.

The stopping sight distance calculation presented by AASHTO has two (2) distinct components: brake reaction time and brak-

t: brake reaction time, 2.5 s; V: design speed, mph; a: deceleration rate, ft/s².

Design stopping sight distances are provided by AASHTO in Exhibit 3-1 of the Green Book, both in U.S. customary and metric units.

Special consideration by the accident reconstruction specialist must be given to roadways on which specific elements require special attention from drivers, two-lane undivided and bidirectional highways where passing maneuvers are permitted, and longitudinal grades of 3% or higher.

The effects of grade on stopping sight distances have also been considered by AASHTO in the Green Book. The effect of grade on stopping sight distances becomes especially relevant when the driver has a negative slope, i.e., when the vehicle is going downhill. The longest possible stopping distance must be provided in such cases. Design stopping sight distances with the effect of grade can be observed in the Green Book’s Exhibit 3-2.

Figure 4 (below): Length of Vertical Curves (Source: AASHTO)

The Green Book recognizes that there are specific areas on roadways that require special attention from drivers. Some examples of the latter are intersections with special design features and large interchanges on freeways. Longer sight distances must be provided for these, which is why AASHTO provides designers a method for determining a decision sight distance. As stated above, the values observed in the Green Book’s Exhibit 3-3 are substantially greater than those provided for stopping sight distance.

Another subject that may arise in court and is related to stopping sight distances is the fact that AASHTO presents no special provision for trucks in this matter. There are no adaptations or additional variables considered when dealing with trucks in the calculation of

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Figure 5: Elements of Passing Sight Distance for Two-Lane Highways (Source: AASHTO) stopping sight distances. However, this is not an omission on AASHTO’s behalf. AASHTO considers the calculations for stopping sight distances to be the same for passenger vehicles as well as trucks, because the advantage in braking efficiency of the former is compensated by the better visibility of the driver’s seating height provided by the latter.

Most roads in the United States and other parts of the world are two-lane, two-way highways on which vehicles approaching others traveling at lower speeds may be allowed to pass these. Enough passing sight distance must be provided to the passing driver in order to be able to complete the passing maneuver safely. According to AASHTO, “passing sight distance for use in design should be determined on the basis of the length needed to complete normal passing maneuvers in which the passing driver can determine that there are no potentially conflicting vehicles ahead before beginning the maneuver.”

Minimum design criteria for passing sight distance is based on a single vehicle passing a single vehicle, as shown in Exhibit 3-4 from the Green Book.

The parameters presented above are based on the following assumptions: • • • • •

Overtaken vehicle travels at uniform speed.

Passing vehicle has reduced speed and trails overtaken vehicle.

When the passing section is reached, driver needs a short period of time to perceive and react.

Passing is completed, at a speed 15 km/h higher than overtaken vehicle.

When passing vehicle returns to its lane, distance between it and opposing traffic is suitable.

Per AASHTO: • • •

d1: Distance traversed during perception and reaction time and during the initial acceleration to the point of encroachment on the left lane. d2: Distance traveled while passing. d3: Distance between the passing vehicle at the end of

•

its maneuver and the opposing vehicle. d4: Distance traversed by an opposing vehicle for 2/3 of the time the passing vehicle occupies the left lane (2/3 of d2).

Additionally, there are two (2) elements that affect passing sight distances: grade, and the frequency and length of passing sections. Although passing becomes easier on downgrades, passing sight distances presented by AASHTO in Exhibit 3-7 of the Green Book should be exceeded in order to allow for safer passing of vehicles traveling upgrade.

Frequency and length of passing sections depends on the type of roadway, and its analysis should have a string focus on context-sensitivity. Different passing conditions exist between urban and rural highways, as well as streets, since traveling purposes vary among them.

As stated previously, specific elements of highway design respond to the roadway’s functional classification. Depending on the users the roadway is destined to serve, the appropriate design vehicle must be selected by the Designer. AASHTO recommends always using the largest possible design vehicle.

This is yet another element that must be analyzed by the accident reconstructionist, in order to assess whether a vehicle involved in an accident was supposed to be using that roadway, and if the corresponding signs and / or warnings were provided to drivers. A common example of this is the prohibition of heavy vehicles in residential neighborhoods. Nonetheless, single-unit trucks are recommended as the design vehicle for local streets and parkways.

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oadside Design Guide, AASHTO, 2011 [3] AASHTO’s Roadside Design Guide, 2011 (RDG) [3] presents the engineering best practices for the design of safe roadsides and the integration of safety appurtenances in highways across the United States. Like the Green Book previously discussed, the RDG has been adopted by other countries as the primary guidelines for the construction of safer roadways.

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Collision Magazine 93

The RDG defines the roadside as, ”that area beyond the traveled way (driving lanes) and the shoulder (if any) of the roadway itself… While it is a readily accepted fact that safety can best be served by keeping motorists on the road, the focus of this guide is on safety treatments that minimize the likelihood of serious injuries when a driver does run off the road.”

There are many reasons that can cause a driver to leave the travel way. Some of these are the following: • • • • • • • •

determining that the clear zone required for a vehicle running of the road to recover varied according to design speeds and topographic conditions governing the roadside.

When a motorist leaves the traveled way and the roadside is not flat, he or she will encounter foreslopes, backslopes, transverse slopes, drainage channels, or a combination of these. AASHTO defines three types of slopes for the roadside environment: • • •

Recoverable slopes: 1V:4H, or flatter; Non-recoverable slopes: between 1V:3H and 1V:4H; Critical slope: steeper than 1V:3H.

Driver fatigue Driver distractions or inattention Excessive speed Driving under the influence of drugs or alcohol Crash avoidance maneuvers Roadway conditions such as ice, snow, or rain Vehicle component failure Poor visibility.

A vehicle encountering a recoverable slope will likely be able to return to the roadway. A vehicle that encounters a nonrecoverable slope will most likely be able to traverse it, but it will reach the bottom of the slope. Finally, a vehicle traversing a critical slope will likely overturn.

Although safety is best served by a vehicle staying on the road, as stated above, the RDG provides guidelines on how to provide the safest conditions for those vehicles that leave their travel way. Thus, the forgiving roadside concept is presented

by AASHTO, which seeks that roadside design provide errant vehicles running off the road a safe, comfortable, and traversable roadside that allows them to recover their trajectory and return to their corresponding traveled way.

Proposed clear zone distances for roadside design are presented

by AASHTO in the RDG’s Exhibit 3-1. These clear zone distances are based on design speeds, design annual daily traffic (ADT), foreslope or backslope conditions, and their corresponding slopes. Distances are presented, as in all cases in the RDG, in metric and U.S. customary units. Curve correction factors for clear zone distances are presented separately and are based on design speed and curve radius.

In order to achieve a forgiving roadside, AASHTO presents the following design options, in order of preference, for reducing roadside obstacles: 1.

2.

3.

4.

5.

6.

Remove the obstacle.

Redesign the obstacle so it can be safely traversed.

Relocate the obstacle to a point where it is less likely to be struck.

Reduce impact severity by using an appropriate breakaway device.

Shield the obstacle with a longitudinal traffic barrier designed for redirection or use a crash cushion.

Delineate the obstacle if the above alternatives are not appropriate.

The reader can immediately notice that AASHTO promotes seeking as many design alternatives as possible prior to the installation of a safety barrier, ranking this alternative fifth out of the six options it presents in the RDG. AASHTO defines the clear zone as “the unobstructed, traversable area provided beyond the edge of the through traveled way for the recovery of errant vehicles.” The clear zone includes the shoulder, when applicable, as well as bike lanes and auxiliary lanes. The latter are considered part of the clear zone when they do not function as through lanes.

When the clear zone concept was initially conceived in the 1970’s, most highway agencies established a 30 ft. wide clear zone as an adequate area for vehicles running off the road to recover and return to their corresponding traveled way. However, continuous studies of accidents occurring on the roadside led to 94

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Figure 6: Clear Zone Distances (Source: AASHTO)

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Figure 7. RDG Exhibit 3-1 (Source: AASHTO)

Figure 8: Example of a Parallel Foreslope Design (Source: AASHTO) www.collisionpublishing.com

Collision Magazine 95

Figure 8 presents an example of a parallel foreslope design, which is provided in the RDG. Backslopes result in roadways that are built on cut sections.

Smooth, traversable clear zones 1V:3H or flatter can be accomplished to provide safe conditions for errant drivers running off the road. When 1V:3V backslopes cannot be accomplished, or protruding rocks that will most likely cause vehicle snagging instead of re-directing, backslopes should begin outside the clear zone or be shielded, according to AASHTO. Transverse slopes occur in medians, when opposing lanes are connected to provide for left-turn or u-turn maneuvers. These can also occur due to driveways, intersections, and other roadway crossings. Although drivers are not as commonly exposed to transverse slopes as they are to foreslopes and backslopes, the impact severity is typically higher due to the fact that the impact is head on, which is why slopes 1V:10H are ideal in these areas, although not always feasible due to right-of-way limitations.

Storm sewer structures usually accompany transverse slopes, in order to provide adequate drainage along medians. Providing adequate traversable appurtenances to these structures is of the utmost importance in order to adequately protect errant

vehicles. Having a traversable and smooth slope is of no use if a vehicle will impact an unprotected and non-traversable fixed drainage structure.

Drainage channels, which are used to collect storm water runoff and are usually located parallel to highway embankments, also need special attention. These channels need to be constructed, operated, and maintained considering the effect they have on the roadside environment when they are located within the roadway’s right-of-way (ROW). These hydraulic structures can easily cause an errant vehicle that runs off the road and falls into one of them to overturn.

As previously stated in this document, AASHTO recommends that a longitudinal barrier or a crash cushion be used to shield an object only when a designer cannot remove or relocate an object, or cannot reduce the severity of an impact by an errant vehicle by installing a breakaway device. Thus, the RDG presents barrier warrants that are based on the premise that a longitudinal barrier should only be installed if it will reduce the severity of potential crashes. AASHTO also reminds the reader that, ”It is important to note that the probability or frequency of run-off-the-road crashes is not directly related to the severity of potential crashes.”

Figure 9: Example of a Backslope, Route 5 South, Chile.

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Longitudinal barriers are selected based on test criteria presented in the NCHRP 350 Report [4] and the recently introduced Manual for Assessing Safety Hardware (MASH) [2]. Six (6) test levels (TL) are presented in both of these documents, which are used to assess occupant risk, structural integrity of the different barriers, and the post-impact behavior of the test vehicles. MASH [2] maintains the test conventions established in the NCHRP-350 [4], but modifies some of the testing requirements, particularly the test vehicles.

Longitudinal barriers can be classified as flexible, semi-rigid, and rigid. These terms do not necessarily make reference to the materials used for the construction of the barrier, but rather point to how each barrier behaves when impacted. Flexible barriers provide for the most deflection and, therefore, can be more forgiving than rigid barriers. However, installation criteria provided by the RDG, NCHRP-350 [4], MASH [2], and the manufacturer, as well as sound engineering judgment are essential when determining which type of barrier to use in every specific situation.

Common examples of flexible barriers include tension-cable systems. Likewise, guardrails and box-beam barriers are classified as semi-rigid barriers. Finally, F-shaped and New Jerseytype concrete barriers are classified as rigid barriers.

When a longitudinal barrier is warranted based on the criteria presented by AASHTO and sound engineering judgment from the Designer, specific barrier design components must be met. The length of need (LON) of a barrier is the length that

is required for a barrier to satisfactorily shield and redirect an errant vehicle back to the traveled way. The LON includes the standard section of a barrier, which is provided by each manufacturer in compliance with NCHRP-350 [4] and MASH [2] specifications; and a transition section from a semi-rigid to a rigid barrier, commonly seen between barriers from a roadway section transitioning to a bridge barrier segment.

A critical aspect of a longitudinal barrier is its maximum deflection, which is obtained from performance testing. In order for a barrier to adequately shield an obstacle, the barrier must be installed with a minimum lateral offset equal to the maximum deflection of the specified barrier. For example, oftentimes a driver can observe a w-beam guardrail directly mounted on a pole or bridge pier, rendering it useless, since its deflection will lead the errant vehicle directly into the fixed object it is supposed to shield.

Another important element that needs to be considered during the design and installation of a longitudinal barrier is the shy line offset, which is the lateral distance beyond the traveled way from which a barrier will not be perceived as an obstacle by the driver. As a general rule, barriers shall always be installed as far away from the roadway as possible, since a barrier is perceived by the driver as an object. A barrier that is installed too close to the traveled way will cause the driver to be “shy” and reduce speed or change lanes. Thus, an adequate shy line offset will prevent driver “shyness” and allow normal traveling along the road.

Figure 10: Traversable Grate Covering Drainage Structure, Orlando, FL.

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Figure 11: Roadside Barriers and Approved Test Levels (Source: AASHTO) Median barriers are longitudinal barriers installed on highway medians. The main difference between roadside longitudinal barriers and median barriers is that the latter have the ability to re-direct vehicles impacting them in opposite directions. Context-sensitivity and case-by-case analysis for the implementation of median barriers is fundamental, since there is no onesize-fits-all recommendation for their use. Median barriers can also be flexible, semi-rigid, or rigid, and must meet the same TL-criteria applicable to roadside barriers.

In order for a longitudinal or a median barrier not to become a hazardous fixed object that a vehicle might impact, appropriate performance-tested barrier end treatments must always be used. Untreated ends of barriers result in serious injuries, because the vehicle is stopped abruptly. Crash cushions and other proprietary end treatments that comply with NCHRP-350 and MASH requirements help reduce the severity of a vehicle impacting an untreated barrier end.

In conclusion, the design guidelines set forth in the RDG for the installation of safety appurtenances are the most effective and performance-based standards available for transportation engineers in order to provide the safest roadside environment possible. When warranted and properly installed, a longitudinal barrier and other safety appurtenances discussed in the RDG will reduce the impact severity of an errant vehicle running off the road. However, a poorly installed barrier may become a hazardous object an errant vehicle could impact.

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As with other design guidelines, the RDG presents the best state of the practice engineering methods for Designers to provide the safest possible roadside environment. These are based on extensive investigation and continuous testing and performance evaluation. Nonetheless, engineering judgment will always be the prevailing tool in the selection of the most appropriate design and safety appurtenances to be installed within a highway ROW. Knowing the fundamental design elements of highway and roadside design can become key tools in the analysis made by a professional accident reconstruction specialist. A complete site analysis might reveal to the accident reconstructionist design, construction, and / or installation deficiencies that could prove to be determining in the analysis of a motor vehicle crash.

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eferences 1. AASHTO. A Policy on Geometric Design of Highways and Streets. AASHTO. 2004.

2. AASHTO. Manual for Assessing Safety Hardware. AASHTO. 2009.

3. AASHTO. Roadside Design Guide. AASHTO. 2011.

4. Transportation Research Board. National Research Council, NCHRP Report 350. Washington, D.C. 1993.

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Figure 12: Guardrail Installed Over Face of Bridge Pier, Alexandria, Virginia

Figure 13: Guardrail Installed Next to Post, Alexandria, Virginia.

Figure 14:Unsecured Barrier End, San Juan, PR. www.collisionpublishing.com

Collision Magazine 99

Now is the time to "get in the game" and incorporate the Bosch Crash Data Retrieval System in your vehicle documentation toolkit. The Bosch Crash Data Retrieval System is a proven (and court admissible) tool that allows Collision Reconstructionists, Law Enforcement, Insurance adjusters and SIU's, investigating vehicle crashes, the opportunity to image crucial event [crash] data parameters from a vehicle that has been in a crash. This crash data, which is stored in the vehicles airbag control module, may be used to make informed decisions about the crash directly from the vehicle in question.

Starting in September of 2012, automobile manufacturers will be required to ensure that new light vehicles equipped with an Event Data Recorder (EDR) in their Electronic Control Unit (ECU), allow EDR data to be retrieved by a commercially available tool, following an "event" [crash]. This is in compliance with the National Highway Traffic Safety Administration (NHTSA) final rule (49 CFR Part 563), that manufacturers will be required to have this capability in place within 90 days of the first sale of such a vehicle into the US market. Currently, the Bosch CDR System supports select GM, Ford, Chrysler, Fiat, and Toyota vehicles along with an recently announced agreement with Mazda and more auto manufactures coming soon.

www.

cdr-system.com 800-280-7940

My

e th

el e Wh

The Mathematics of a Bicycle Going Down an Incline

rn u T

at

Peter Bergh

A

ssumptions and notation We assume that the bicycle, under control of its rider, is rolling down a constant-slope incline and that the wheels are rolling without slipping. The rider may be braking, pedaling, or coasting. If he is braking or pedaling, we assume that he maintains a constant pedaling rate or brake pressure, so that the effects of the rider’s actions are reflected in a constant additional acceleration or deceleration of the equipage. Furthermore, we assume that the wind speed, projected parallel to the equipage’s path, is constant.

We use the following notation: • • • • • •

The slope angle of the incline is θ.

The total mass of the bicycle and rider is m.

The radius of each wheel of the bicycle is r w and the mass of each wheel of the bicycle is mw.

The initial velocity of the bicyclist is v0, which is assumed to be positive or zero.

The velocity of the wind, projected parallel to the path of the equipage, is vw. We adopt the convention that a head wind is positive and that a tail wind is negative.

The drag factor for the bicycle is f. If the equipage is coasting, this is the rolling coefficient of friction. If the rider is braking, f is the deceleration factor caused by his braking and by the rolling friction. If the rider is pedaling, -f is the acceleration factor caused by his pedaling and by the rolling friction.

M

oment of inertia for a wheel We assume that, in respect to rotation, a bicycle wheel can be represented as a homogenous circular disk of radius ri, representing the hub and spokes, and mass pmw (where p is a (fairly small) fraction of the wheel’s mass) and a homogenous circular ring of radii ri and rw, representing the rim and tire, and, of course, mass (1-p)mw.

We note that the density of the circular disk is:

and that the density of the circular ring is

Using the standard formula for the moment of inertia around an axis orthogonal to the wheel and passing through the center of the wheel (see, e.g., Bronshtein, p 480), we get

T

he equation of motion We follow Goldstein, p. 23:

where qj is a generalized coordinate and a dot denotes differentiation with respect to time, L=T-V, T is the kinetic energy,V is the potential function, and Qj is the generalized force corresponding to qj.

We introduce a coordinate axis with the origin at the starting point of the bicyclist and increasing down the slope. We call this coordinate x. At any given time, the angular velocity (in radians per second) of each wheel is .

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The kinetic energy is composed of the kinetic energy from accelerating down the slope and the kinetic energy from the two rotating wheels.

Thus, we get

S

olving the equation of motion Dividing equation (1.1) by m+kmw and setting

,

and Setting

we get an equivalent equation

we get our final expression for the kinetic energy

The potential function is simple:

We note that setting the wind velocity as

(1.2) to zero gives the terminal velocity plus

so the Lagrangian is

The generalized forces (in this case, the forces) are the air resistance and the friction. Both of these oppose the motion, so they have negative values. The friction is simple: Qf=-mgfcosθ.

The air resistance is

The bicycle’s velocity will asymptotically approach the terminal velocity, as demonstrated below. Some conditions on v0, vt, and vw must be satisfied (for details, see below), or there is no valid solution. This equation can easily be solved by separating the variables:

where p is the density of the air, S is the surface area of the cyclist and the bicycle (as seen at right angles to the direction of motion), and C is a dimensionless drag coefficient.

Thus, the force is

Putting the various quantities we have derived into the Lagrange equation, we get the equation of motion:

Integrating (the integral is given on, e.g., p. 1027 of Bronshtein), we get

where C is a constant of integration. Solving for v, we get

(1.3) (1.1) Note that setting mw, f, and p to zero reproduces the standard equation for a particle sliding down a frictionless incline

where C1=(vt+vw)C. Integrating again, we get the solution to (1.1) (and (1.2)) as (see, e.g., Bronshtein, p. 1051)

where C2 is another constant of integration.

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(1.4)

F

inding the constants of integration We get the values of the constants of integration from the initial conditions:

For t=0, we have v=v0, so

We note that this implies some conditions on v0, vw, and vt, since the hyperbolic tangent always is between -1 and +1: - If there is a head wind or no wind (vw≥0): v0<vt - If there is a tail wind (vw<0): v0<vt and v0+vt=-2vw For t=0, we have x=0, so (1.5)

A

pproximations for large values of t For large t, we can approximate v and x as follows.

First we note that, for large values of t,

is close to 1 so that v (equation (1.3)) asymptotically approaches vt when t grows towards infinity. Thus, we see that vt is, indeed, the terminal velocity for the equipage.

Second, for large values of t:

Inserting the final result of (1.5) into (1.3), we get an explicit expression for the velocity after the bicycle has traveled for a given distance.

In the more complicated case, when vw is different from zero, the value of the time is most simply obtained numerically. A suitable approach is to use a multiple of the approximate time value calculated above, together with the time zero, as bounds for a binary search for the root. Of course, once the time has been calculated, we substitute the calculated time into (1.3) to get the desired velocity.

Implementation note Bronshtein tells us, on page 92, that

and that

so it is easy to program the inverse hyperbolic cosine and tangent on a computer.

Solving this last equation for the time, we get

D

isregarding air resistance This is most easily done by setting p in (1.1) to zero.

We get

The right hand side is constant, so we integrate and, remembering that This approximate equation for the time will come in handy when we solve numerically for the time.

F

inding the velocity after the equipage has traversed a given distance Often, when reconstructing a crash, we have the distance (i.e., x) but not the time. Thus, we need to solve (1.4) for the time. In the simple case when vw is zero, i.e., there is no wind parallel to the path of the equipage, we get:

get (1.6) (we know that the velocity at time zero is v0.)

(1.7)

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(we know that the x coordinate at time zero is 0.) Solving (1.7) for the time, we get

(i.e., the equipage is coasting), an outer wheel diameter of 27 inches, an inner wheel diameter of 25.5 inches, and assume that ten percent of the wheel weight is “used up” by the hub and the spokes. We furthermore assume that the rides take place in still air. The density of the air has been taken from the U.S. Standard Atmosphere, as reproduced in CRC, p. 14-19.

Table 1 shows the results of calculating the speeds when taking air resistance into account and when ignoring air resistance. In each cell, the first number shows the speed in MPH when taking air resistance into account, the second number shows the speed in MPH when disregarding the effect of air resistance, and the third number shows the speed loss in percent of the speed when disregarding the effect of air resistance.

α will normally be positive, unless the slope is very low (less than about one degree for a typical rolling friction of around 0.015), so we get

(1.8) and, as before, we substitute this into (1.6) to get the velocity at the end of the incline.

H

ow important is air resistance?

We calculate the numeric values for the speed at the end of an incline of 100, 150, and 200 feet, with incline angles of 1, 2, 3, 4, 5, 6, 7, 8, 9, and 10 degrees.

We use the formulae taking air resistance into account and the formulae for when air resistance is ignored. We use a bicycle weight of 20 lb., a wheel weight of 1 lb., a rider weight of 100 lb., an initial speed of 1 mph, a rolling drag factor of 0.014

Angle of incline in degrees 1 2 3 4 5 6 7 8 9 10

As is obvious from the table, the effect of air resistance on a bicyclist that’s going down an incline is significant; the air resistance slows the bicyclist down by some 15 to 30 percent over distances of 100 to 200 feet. It is interesting to note that the percentage of slowdown depends only weakly on the slope of the incline.

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eferences Bronshtein: I.N. Bronshtein, K. A. Semendyayev, G. Musiol, H. Muehlig, Handbook of Mathematics, Fifth edition, Springer 2007, ISBN 978-3-54072121-5.

CRC: CRC Handbook of Chemistry and Physics, 86th edition, edited by David R. Lide, CRC Press 2005, ISBN 0-8493-0486-5.

Goldstein: H. Goldstein, C. Poole, J. Safko, Classical Mechanichs, Third edition, Addison Wesley 2002, ISBN 0-20165702-3.

100 feet 2.89 6.90 9.32 11.23 12.86 14.30 15.61 16.81 17.93 18.99

3.34 7.91 10.68 12.86 14.72 16.37 17.87 19.24 20.53 21.73

150 feet 16 15 15 15 14 14 14 14 14 14

3.28 7.92 10.71 12.91 14.79 16.45 17.95 19.34 20.63 21.84

4.03 9.67 13.06 15.74 18.02 20.04 21.87 23.56 25.13 26.60

200 feet 23 22 22 22 22 22 22 22 22 22

3.54 8.61 11.65 14.05 16.09 17.90 19.53 21.04 22.45 23.77

4.62 11.15 15.07 18.16 20.80 23.13 25.25 27.20 29.01 30.71

Table 1: The results of calculating the speeds when taking air resistance into account and when ignoring air resistance.

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31 30 29 29 29 29 29 29 29 29

Eccentric Collisions and

Post-Impact Motion Busting a Myth

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I

ntroduction A common misconception among a number of reconstructionists is that if two vehicles collide with collinear velocities, each can exert a force only in the direction that it was initially traveling, even if the collision velocities are eccentric (also called an offset collision), although there is no physical law that requires that relationship. This misconception has led some to form rules (actually myths) regarding the post-impact motion of a vehicle after colliding with a rigid object or after colliding with another vehicle that is originally stationary or moving in a parallel direction.

Bruno Schmidt, Schmidt Consulting Services Michelle Beach, Michelle Beach Consulting the quadrant, or the cone of departure, defined by their approach velocities. While this rule is generally applicable for vehicles whose approach angles define a quadrant provided they more or less move off together, there is not a fundamental law of physics that says the departure angles must lie within the approach quadrant.

Sometimes Newton’s Laws of motion are “invoked” by a reconstruction to justify the use of the rules above. However, Newton’s Laws say nothing directly about the relationship between an approach velocity Closely related to that misconception is the rule that and the direction of the collision force nor about the the departure angles of colliding vehicles must be in cone of departure. All they say is that force equals www.collisionpublishing.com

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mass time acceleration (which will be in the direction of the ∆v vector), and that momentum is conserved during a collision where external forces do not contribute to the momentum.

Current literature argues against those rule-myths1,2 but they continue to exist. This paper explores some examples of those rule-myths, and provides the results of crash tests, both real and simulated, that indeed show those rule-myths are not universally true.

E

xample 1 The departure angles of both vehicles do not have to lie within the cone defined by the approach velocities.

A departure from this general rule can occur in a collision where the two momentum vectors are of greatly different sizes and where the collision is very eccentric. The effect of an eccentric collision is for the force to have a lever arm which causes the vehicle to rotate. If the rotating vehicle has a small momentum to begin with, then the rotation, combined with the effect of rotation around the contact area, can cause its resulting post-impact momentum to lie outside the cone of approach. This was demonstrated at the October 2009 Joint Conference held in Ocean City, Maryland with an eccentric collision between a slowly moving pickup and a more rapidly moving semi tractor-trailer.3 It should be pointed out that the departure angle was quite small relative to the cone of approach, and in a different context, one of the authors has heard the argument that roadway friction could have affected the departure angle.

E

xample 2 The departure angles of both vehicles do not have to lie within the cone defined by the approach velocities.

To confirm the fact that a departure angle indeed can lie outside the cone of approach, a simulation was performed, using the SMAC feature of REC-TEC.4 The results of that simulation are shown in Figure 1. Note that prior to the collision, the momentum component in the y-direction is positive. Afterwards, vehicle 1 acquires a positive y-component of

momentum, and vehicle 2 acquires a negative y-component of momentum. The algebraic sum of the two post-collision y-components of momentum equals the pre-collision momentum of vehicle 2. The simulation was performed with the coefficient of roadway friction set to zero, so roadway friction played no role in determining the post-impact momentums of the two vehicles. This simulation clearly shows that under the right circumstances, a departure velocity does not have to lie within the approach cone.

E

xample 3 A vehicle is capable of exerting a collision force prior to maximum engagement that is not in the direction that it was initially traveling, even if it strikes a fixed barrier.

We have heard experts express the mistaken concept regarding a collision force with a rigid barrier as being required to be in the same direction as the velocity vector claiming that the vehicle can only exert an “oomph” in the direction it is traveling. However, the direction of the collision force is also determined by the changing structure of the vehicle, and can be at an angle to the original velocity vector. One thoughtexperiment to illustrate this is to consider an offset collision into a fixed pole. The vehicle will continue to move forward (at a reduced velocity), and it will rotate around the contact point with the pole. This requires that the vehicle’s center of gravity move laterally as the vehicle rotates, which would require a lateral force vector, perpendicular to the original vehicle motion.

When presented with this thought-experiment, another expert, after some thought, acknowledged that indeed would happen, but opined that it would not occur prior to maximum engagement; that the lateral collision force would occur during the restitution phase of the collision.

To examine these arguments, one can study offset rigid barrier collisions conducted by the Insurance Institute for Highway Safety (IIHS).5 Some sequential screen captures of the video of one such test are shown in Figures 2 through 5.

Figure 1: SMAC/RECTEC simulation results 110 Collision Magazine

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Note that it is clear that a significant lateral force is created, as the vehicle rotates and moves off to its right. To address the question of when that lateral force is generated during the collision (before maximum engagement, at maximum engagement, or after maximum engagement), one can trace the path of the center of gravity and determine the changes in x and y as time progresses, and from that, evaluate the values of Vx and Vy as time progresses, as shown in Figures 6, 7, and 8, where a series of dots were placed over the center of gravity locations every eight frames in the video. The red dot and green dot show maximum engagement and separation, respectively.

The measured x and y values, and the calculated Vx and Vy values, are displayed in the spreadsheet in Figure 9. Note that the x-axis is fixed in the original direction of motion of the

First Contact

Maximum Engagement

Initial Separation

Figure 2 - 5 (top to bottom): Sequential screen captures of test video

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Figure 6 - 8 (top to bottom): Test video with a series of dots were placed over the center of gravity locations every eight frames

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Figure 9: The measured x and y values and the calculated Vx and Vy values vehicle. From the graphics in Figures 6 and 7 it can be observed that there is a noticeable change in the y coordinate of the center of gravity prior to maximum engagement, and the spreadsheet shows that the entire change in Vy occurs prior to maximum engagement. This conclusively demonstrates that there is a significant lateral collision force, and it occurs prior to maximum engagement, not after.

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onclusions While some guides (such as the departure cone) can be useful in evaluating most collisions that are encountered, they are not absolute rules, and may very well not apply in highly eccentric collisions. Likewise, the myth that eccentric collisions will not produce lateral motion, except perhaps after maximum engagement, does not apply in general.

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As previously mentioned, some have held the opinion that any eferences significant lateral forces would develop only after maximum 1. Daily, Shigemura, and Daily, Fundamentals of Traffic engagement is reached. To address that point in more detail, an Crash Reconstruction, Institute of Police Technology analysis has been performed of the contribution to the PDOF and Management, 2006 prior to maximum engagement. Using the spreadsheet values of Figure 9, ∆Vx = -40 mph and ∆Vy = 10 mph. Note that 2. Fricke, Traffic Crash Reconstruction, 2nd ed., Northwestthese components are expressed in terms of an earth-fixed co- ern University Center for Public Safety, 2010 ordinate system which matches the vehicle coordinate system only if the vehicle doesn’t rotate. One can then calculate the 3. Bartlett and Schmidt, “Cone of Departure: A Good Idea, PDOF, in terms of the earth-fixed coordinate system, by evalu- But Not a Law,” Collision Magazine, Fall 2010 ating the cotangent of ∆Vy/∆Vx for a value of 14 degrees (or -14 degrees, depending upon the sign convention used). (For 4. Bonnett, www.rec-tec.com those not familiar with using an earth-fixed coordinate system for describing the PDOF, see pages 266 and 267 of reference 5. IIHS Crash Test CEF0715 video 2.) Using an exemplar vehicle oriented at the same angle as the http://www.youtube.com/iihs#p/u/365/XAV2N4pdgDE screen capture of the crash video at maximum engagement, it can be seen in Figure 10 that the vehicle has rotated counterclockwise approximately 4 degrees Figure 10: exemplar vehicle oriented at the same angle as the screen capture of from its initial orientation parallel to the earththe crash video at maximum engagement fixed x-axis, so the PDOF, relative to the vehicle coordinate system, has a magnitude that is 4 degrees smaller than the earth-fixed PDOF. Using the standard sign convention for the PDOF in a vehicle coordinate system, the PDOF therefore is -10 degrees.

There is an additional small amount of change in Vx after maximum engagement as the vehicle rebounds, and if that were taken into consideration, the PDOF would change by slightly more than one degree.

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Book Reviews

from the desk of Joseph E. Badger Forensic Aspects of Driver Inexperience and Accident Causation Let’s see. In 1996, Lawyers & Judges Publishing Company released Forensic Aspects of Driver Perception and Response

by Paul Olson (3rd Edition, 2010) and Forensic Aspects of Vision and Highway Safety by Merrill Allen (3rd Edition, 2008). Now just off the L&J presses August 1, 2011 comes Forensic Aspects of Driver Inexperience and Accident Causation

by Scott Walmsley.

The first two items were penned by vision gurus, a Ph.D. in Industrial Psychology and a Professor Emeritus at Indiana University’s School of Optometry.

This new 614-page tome,

by Scott Walmsley is not so much about vision or nighttime driving, but rather the author details over 50 skill deficiencies common among inexperienced drivers that increase collision probability, describing how these affect perceptions, judgments, behaviors, reactions, decisions, and actions.

From this information, the reader learns how particular skill deficiencies associated with inexperience combine with specific traffic scenarios and result in critical driving errors. All of these errors occurred with frequency and predictability across the range of inexperienced drivers, giving the reader insight into the human factors that are statistically common among inexperienced drivers.

Mr. Walmsley began writing the book in the autumn of 2005 and completed it five years later; however, the data collection process began 10 years earlier.

I asked Scott why he wrote the book in the first place. “I wrote the book to address many of the common misconceptions about why novice drivers are involved in a disproportionate percentage of collisions. I wanted to provide the most accurate, detailed and extensive information based on how inexperienced drivers perform in actual traffic situations as opposed to simulated environments.”

I found a number of neat facets of Walmsley’s book; for one, he does not have page after page of voluminous continuous text. Although there are 20 chapters, most are subdivided as in Chapter 10A, Chapter 10B, Chapter 10C and so on.

Moreover, the author subdivided each chapter into quick, easy-to-read one-to-three paragraphs. This is great for those with short attention spans who read books saying, “Come on, let’s go.”

Forensic Aspects of Driver Inexperience and Accident Causation topics include: 114 Collision Magazine

• • • • • • • • • • • • • • • • • • • • •

Task Execution Process Fifty-Two Skill Deficiencies of Driver Inexperience Unprotected Left Turn Collisions Head-On Collisions Crossing the Centerline Entering Arterials from Stops Collisions Occurring While Entering Traffic from a Curb Collisions Occurring on Approach to Intersections Prior to Turns Collisions Involving Loss of Vehicle Control on Turns Curve-induced Collisions Vehicle-Pedestrian Collisions Uncontrolled Intersection Collisions Vehicle-Bicycle Collisions Vehicle-Motorcycle Collisions Lane Change Collisions Merging Collisions Right Turn on Red Collisions Left Turn on Red Collisions Collisions Occurring During Multiple Lane Turns Collisions at All Way Stops Rear End Collisions

He saved what in my opinion is his best chapter, Rear End Collisions, for last. In this chapter, as others, he discusses, in detail, numerous errors committed by drivers.

Such errors include: Insufficient Following Distance; Failure to Increase Following Distance in Reaction to a Vehicle Entering the Lane of Travel; Failure to Conform to Changing Traffic Flow Speeds Within the Required Distance; Inability to Stop the Vehicle in a Sufficiently Short Distance; Failing to React to a Vehicle Entering the Travel Lane from a Stop; Failing to Stop a Sufficient Length Back from the Lead Vehicle; and Not Anticipating the Lead Vehicle Stopping When Entering Traffic from a Stop.

And more.

The nice part about all those Errors, is that Mr. Walmsley presents solutions, that is, how to prevent such errors while driving. He offers methods for instructing student drivers and those already licensed but inexperienced drivers. (Even veteran motorists who have been driving for years will benefit by the suggestions.)

I particularly liked Error 12 in the final chapter: Errantly Assuming that the Forward Vehicle Should or Will Accelerate.

This I am sure will be a more prevalent problem when the forward vehicle’s driver is on a cell phone and fails to move when the light goes green.

What are some of the problems of newbie motorists? In an email to me, Walmsley said, “Improperly slow speeds can cause as many hazards among inexperienced drivers as excessively high speeds,” for one. For another, “Novice drivers frequently have difficulty perceiving speed, they might believe they are traveling 35 M.P.H. when in fact their speed is 50 or 20.”

www.collisionpublishing.com

One more: “A common trait of inexperience is ‘tunnel vision.’ Inexperienced drivers commonly fixate directly in front of the vehicle to the exclusion of critical lateral and forward zones.”

Betwixt and between the book’s sections are over 850 extremely well executed diagrams that took the author nearly a 1000 hours slaving over a program called “Quick Scene” (which may be purchased be purchased from http://www. cadzone.com/).

Traffic Accident Investigation: A Training and Reference Manual Some of you may have read a while back my book review titled “The Last Book R.W. (Bob) Rivers Ever Wrote.”

Well, guess what. Yep, he went and wrote another. But wait. It is not a new book.

Well, wait. Yes, it’s a brand new book but it is a “3rd Edition, revised 2010” of his 1988 work Traffic Accident Investigation: A Training and Reference Manual.”

You may by chance open the book to such a statements as “… when the driver experiences excessive fear to the level where she believe it is affecting her abilities…” [Page 71] or “As with all driving tasks, an inexperienced driver has a responsibility to acknowledge her limits of ability and stay within those limits until she develops to a level that allows for the safe and consistent execution of those specific tasks.”

[Page 73] [Underscored emphasis mine.] Author Walmsley is not picking on women drivers. In an effort to avoid those bad grammar methods of avoiding gender specific statements employed by many writers, Scott chose to alternate gender references.

Ergo, it is a new and improved old book, published by the Institute of Police Technology and Management (IPTM).

In Chapter 3B, Error 1 (Failure to Accurately Estimate the Speed of Oncoming Vehicles) addresses elemental factors involved in gauging the closure rate of an approaching vehicle. An oncoming car may be speeding excessively, driving at the speed limit, or at what the author calls “common speed.”

IPTM's blurb about the book says this new edition “has been updated and expanded,” yet what I found interesting – I never saw the first edition, but I have the 2nd ed. (1995) – I noticed that the 3rd edition has 66 fewer pages, so I wondered what Rivers omitted and what, specifically, was “expanded.”

I am certain you know of many streets and highways where virtually everyone drives 10-15 mph (or 16-24 kph) over the speed limit. That would be the common speed.

So I asked the author.

“When drivers can estimate the speed of an oncoming vehicle (using their knowledge of the common speed), that known factor can be used to help them more accurately judge the unknown factor of how long it will take that approaching vehicle to arrived at a fixed point.”

Of the book, the publisher’s website offers: “This highly original book is equally useful to legal professionals, accident reconstructionists, insurance professionals, and driver education instructors, among others.” It probably wouldn’t hurt if parents of 15-year-olds got a copy for their about-tobecome-inexperienced drivers.

Should you wonder what sort of a background credentials the author has to put together this ambitious presentation, Scott Walmsley is licensed by Washington State as a Traffic Safety Educator and he spent16 years training new drivers and analyzing the causational factors of collisions that result from inexperience. He has conducted over 17,000 on-street instructional/evaluation sessions involving approximately 3,200 new drivers over those 16 years.

Mr. Walmsley may be reached at DriveEd@Gmail.com, 206-571-8334 (Voice Mail: 206-524-4823) and at the website he administers, www.driverexperience.com (Accord to Scott, the latter will not reach its full function until late September 2011.)

Forensic Aspects of Driver Inexperience and Accident Causation may be obtained by contacting the publisher: Lawyers & Judges Publishing Co., at http://www.lawyersandjudges. com/productdetails.cfm?SKU=4624 or by emailing sales@ lawyersandjudges.com or by calling 1-520-323-1500.

www.collisionpublishing.com

He said, “In general, there have been many new and several up-dated photographs throughout the manual that provide more clear and definitive explanations of the written text or subject matter. All of the materials that have proven over many years to be of importance and correct in the traffic crash investigation field, have been retained, and where necessary amended to reflect contemporary, proven practices.”

I wondered: Such as?

“Examples [are] found in the areas of using drag sleds, drag factors and coefficients of friction. In addition to well-defined diagrams of measuring ‘yaw,’ as prepared by the author, the proper method of measuring yaw for speed analysis, using a team approach, is presented photographically, (for which he credits the West Chester, Ohio, Police Department.)”

Rivers went on to add, “Included in this revised 3rd edition are recently revised U.S. Department of Transportation Charts that encompass a Hazardous Materials Marking, Labeling and Placard Guide, Warning Labels, Placards, with General Guidelines on the Use of these, all of which were supplied by the U.S. DOT Research and Special Programs Administration, Washington, DC.” I have known Bob Rivers for a long time, having met him at IPTM back in the day (whenever that was), but I thought the reader might like to know more about him.

Bob spent 33 years with the Royal Canadian Mounted Police. With the rank of Inspector, he retired in November 1985. Most of his time was spent in traffic crash investigation and traffic law enforcement fields that included onroad investigations, research, training, planning, and program development.

Collision Magazine 115

He has authored over a dozen books and manuals relating to the AI and AR fields, which are sold, distributed and used internationally. Additionally, Bob recently reviewed and analyzed the work done by a team of Russian traffic crash investigators that took place in 1934, during the Stalin era, where it was felt blame might have been improperly placed on the driver of a vehicle involved in a fatality. This work done by Bob is reported in an 833-page book titled The Kirov Murder and Soviet History, published by Yale University Press, 2010, written by Matthew E. Lenoe, Associate Professor of History at the University of Rochester.

Now you know as much about R.W. Rivers as I do, except the part about how nice a guy he is.

Rivers’ research and related book program development has seen Bob travel internationally to various countries in the Pacific and European regions, including South Africa.

Moreover, in keeping with the international theme of this text, all concepts and examples are completed in both U.S. (Imperial) and S.I. units (Système International d'Units).

Example problems that have mathematical solutions are solved in both measurement systems. Bob’s introduction allows the reader to become conversant in both.

An at-scene Traffic Crash Investigator’s Inventory is expanded and included in this revised edition.

Further, an explanation of the Series of Events (which comprise the overall traffic crash scenario) is retained in this 3rd edition, complete with related explanatory detail and diagrams. These events follow the same or similar format first established by the author with his first publications in the 1980s. This format allows for a reconstruction of a traffic crash from the first point of contact to the conclusion of the at-scene investigation.

Updated topics in this revision reflect changes and techniques currently accepted in the professional traffic crash

investigation field.

Example problems are included throughout the text to provide direction for the reader in the application of mathematical principles. These examples of varying difficulty are presented in order to develop the reader’s investigative and mathematical skills.

Contained as part of specific topics throughout the text are traffic crash examples to solve, intended to measure the reader’s or student’s comprehension of the material presented. These examples are intended also to assist them in developing mathematic skills that are so important not only to functioning as professional traffic crash investigators, but also to advance themselves to working in the traffic crash reconstruction field.

A side note: In 1995, this manual was translated into Japanese and forms the basis of Japan’s traffic crash investigation programs.

Even if you own both the First and Second editions of Rivers’ book, you will want the Third to complete the set.

Plus, you will have the latest word on the subject.

The book is available directly from IPTM and probably the easiest way to get it is through their website (www.iptm. org). However, this link takes you right to the Rivers book: http://www.iptm.org/webstore/p-57-training-and-reference-manual-for-traffic-crash-investigation-new-3rd-edition.aspx About the reviewer: Joseph E. Badger is an internationally known accident reconstructionist who has had over 100 articles published in such periodicals as Law and Order magazine, Accident Reconstruction Journal, Accident Investigation Quarterly, and others. Having retired after 20 years with the Indiana State Police, Mr. Badger resides in Bloomington, Indiana.

n o i n i p O

Peer reviewed papers,

the SAE and Collision Magazine mutually exclusive concepts?

T

By W. R. Rusty Haight

he recent suspension of the Accident Investigation and Reconstruction Practices Committee (AIRP) by the Society of Automotive Engineers (see also the letter from the Editor in this issue) ignited discussions regarding the future of papers at the SAE meetings (specifically the next International Congress) and then spilled over to the issue of articles and papers in Collision and whether or not they’re “peer reviewed.” To some, these might seem to be two separate issues, to me, I see they’re really intertwined.

differences in semantics or develop that part of the discussion further, there has to be a starting place, so, for the purposes of this narrative, I’ll set the initial ground rules. (If one is to clearly discuss something, conventions have to be set.) In that regard then, I will hold, for purposes of this narrative, that “peer review” is designed (and that’s an important word here), as I've seen it summed up, to be: "the evaluation by fellow specialists of research that someone has done in order to assess its suitability for publication or further development."

When the AIRP was suspended, the first public discussion wasn’t focused on “how can we get out from under the suspension and rebuild the AIRP?” rather it was “with the AIRP suspended, where are we going to publish our papers at SAE so that they’re still “peer reviewed”?!” While paraphrased here, the implication and misunderstanding was that it was the AIRP who/which was “responsible” for promulgating the crash reconstruction technical papers within SAE when, actually, the SAE “...Land & Sea Group oversees the technical content provided in all of the ground vehicle-related conferences that SAE offers...” (From an email by Colette Wright, Manager, SAE Automotive Technical Programs). For years, this has been the case; however, the representation of the papers has been somewhat less clear (perhaps less straightforward is a better way to put it) which has demonstrably lead to the resulting confusion.

uitability for publication To me, that’s the key here. What’s suitable for publication? To what audience? For what ultimate purpose?

The technical sessions at SAE meetings where the papers were presented (particularly at the International Congress) were (1) organized by well known, members of the AIRP and it was (2) those same members who were also identified with “task forces” (or similarly named sub groups) within the AIRP and (3) virtually all those reviewing papers were those same active members of the AIRP. The “connection” between SAE (Land and Sea Group) published papers and the AIRP - although technically in error - was apparent to even the most casual observer and, as a result, those published could (and have) claimed that they had papers “reviewed by the AIRP and published by the SAE’s AIRP.” As plainly incorrect as that statement is, by way of perception given outward appearances, that it was an easy connection to claim and a connection even those otherwise actively involved in the AIRP made by virtue of the overlapping activities of the individuals.

So then, what’s the “benefit” of having a paper published by the SAE? Until late, one could claim such paper was “peer reviewed by the SAE AIRP;” however, I would argue that such an assertion is, at best, one made in name only and, in practical application, a meaningless distinction. Adding that the “AIRP reviewed it” was a misrepresentation but one made often and never questioned for the reasons previously stated.

To further this discussion, I think we have to ask: what is “peer review” and what is it “for?” While I stand ready to discuss 118 Collision Magazine

S

On the one hand, I will hold that what one sees as “suitable” another may not. Here, I think is the flaw in peer review.

By way of analogy, if Galileo, da Vinci or Newton had been subject to AIRP-style peer review conducted by the church, it (the church) would have rejected ALL of their writings which, given the orthodoxy of the AIRP, is a pretty apt analogy. In that example, the church was deciding, based on an established orthodoxy what was suitable for publication.

Moreover, the truth is that calling something "peer reviewed" simply does not make it somehow “more worthy” than another article or document particularly when the process fails to eliminate reviewer bias and THAT has been a long standing complaint as it relates to that "process" at SAE (particularly with the overt connection to the as established AIRP). For years, the SAE with the AIRP connection has been a textbook example of elitism, a lack of anonymity of the reviewer OR author highlighted by jealousies and efforts at a competitive advantage (no doubt something that figured into the HQ letter's description of the make up of the committee). In practice, in this context and often elsewhere, peer review demonstrably fails to weed out fraudulent or flawed research and it cannot guarantee either the truthfulness or the validity of the work particularly when the focus is NOT on a reviewer as "someone who had an understanding of the topic" and the review is instead on methodology or the maintenance of an established orthodoxy.

“Suitable for publication” took on, within SAE as it related to crash reconstruction papers and as shepherded by members of the AIRP, a mantle of publishing almost as though it were some sort of a reward for being part of the AIRP team. The paper’s actual worth (suitability) wasn’t as often so much the focus as it was “who was the author and would it be good resume fodder?”

Publishing with SAE has been for too many for too long nothing more than an opportunity for resume enhancement. The AIRP has, as it was once described, been a "society of professionals:" but, in my opinion, became a demonstrably inef-

www.collisionpublishing.com

“

fective social club while not designed to, surely acting almost exclusively to enhance individual credentials and give some legitimacy to the "members" and session organizers whom now no longer have the apparent legitimacy of an SAE committee behind them inasmuch as papers can still be published by the Land and Sea Group.

Which then brings us to Collision. When there was first talk of creating a new publication, there was a discussion of implementing a “peer review” process on a couple of levels. On one hand, well meaning, qualified individuals volunteered to act as reviewers and some papers were tentatively “reviewed” early on. Then we ran into the notion of “suitability for publication” and the underlying idea that Collision is a regular periodical, not a once a year opportunity to publish a paper without the clear and direct opportunity for followup dissenting opinion or position and, frankly, the idea that we’re running a magazine: a vehicle to get information out, and like the work or not (and there was some I didn’t like) getting it out there was better than stifling it in the larger scheme of things.

Looking at publication deadlines and not wanting to fall into the trap of being one or two years behind in publication dates waiting for reviews, changes and resubmissions, we opted for an approach that embodied the idea that “almost everything is “suitable” for publication” and we’ll openly and actively welcome opposing views and provide the opportunity for someone to write a rebuttal or critique of a previously published piece. The idea is/was that as long as the piece was coherent and topical - about a reconstruction related topic - why not give it the widest audience and then let the community review and respond.

That policy remains in effect today. We could print an issue of the responses, critiques and reviews we’ve received on previously published articles; however, it would be a short issue with a lot of blank pages. While there are many who would decry content in Collision, none have been bold enough to counter it. While there are some who would suggest that if you “fail at SAE (you can) publish in Collision” which ignorantly assumes the SAE has some corner on the market or sets some actual standard on what is and is not “suitable for publication.” I contend it simply does not and anytime cronyism undermines an otherwise potentially meaningful process, it makes the process essentially meaningless.

On the other hand, we offered, to Collision’s premier industry partner and the organization that was instrumental in starting Collision - NAPARS - the opportunity to establish a peer review process. We have long made the offer that papers or articles submitted by an author to NAPARS for review could be highlighted as "reviewed" in each issue but no one there's ever taken us up on that offer.

In an attempt to level the playing field, we’d do something else different than the way it was done at SAE, our proposal was to establish a NAPARS backed review group to draw from, run by NAPARS at their Board's pleasure. For the definition of "peer," I'd recommend only those why have completed the ACTAR Accreditation but that's just a recommendation so that we can set a certain common experience level to call a "peer." I would suggest NAPARS could ask for volunteers from the NAPARS membership, explain the requirements and then ask for their areas of expertise (i.e.: pedestrians, CDR, momentum, drag sleds...whatever it is) or areas they're interested in reviewing papers on and their qualifications in that area.

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Why not give it the widest audience and then let the community review and respond?

Then, when a paper comes in, the NAPARS coordinator would randomize the list by expertise/interest and randomly pick reviewers. If we get, say,10 people willing to do reviews in a certain category, depending on the number of papers submitted, they might have to look at no more than one per year, maybe two. For the volunteers, it's not an onerous commitment that way and for the author, it means he's unlikely to find someone whom he deals with professionally as his reviewer.

Blind reviews in this business are tough. I know that if I see certain cars in a photo or certain instruments, I'm going to have an idea of who is doing the work. Admittedly not everyone will have that level of familiarity but that might be addressed either by way of a question to the reviewer about whether or not they recognize the author from the work and are willing to recuse themselves if they do.

Collision editorial staff, myself included, would act only as editorial review beyond that. We'll handle the formatting for the magazine and where there's a rejection, we can (not "will") offer the author an UNreviewed spot in Collision. If there's an appeal on an issue, I should think it would go to the NAPARS coordinator first then us (where we can again offer the UNreviewed publication option. Normal journals (i.e.: JAMA) have both peer review and editorial review. I think that is appropriate here and if the NAPARS coordinator, and Collision staff recuse ourselves from doing the actual reviews, that might work to deflect later suggestions of cronyism. (Notably no such option exists at SAE thus limiting the distribution of work that doesn't meet the presumption of acceptance within that smaller group formerly representative of the AIRP membership.)

I'm in favor of a fair review process of work which SHOULD be subject to peer review not, as is far too much the case at SAE, "reviewed" for the sake of being able to say it was reviewed when there really is no new ground covered. (Honestly, I see few things in AR these days meeting that threshold but I'm willing to print almost anything a NAPARS sponsored review committee would see fit to review and pass on as such.) At the same time, I stand by the position that any reasonably related information, something someone in the field might find useful should get the widest possible distribution.

So, are the SAE, Collision and the concept of peer review mutually exclusive concepts? I don’t think so. I think there’s room for a reasoned and realistic review process of work that needs to be reviewed but I also believe that giving the widest distribution to relevant information which can always be countered - just like an SAE paper can be (and has been) - is the more responsible way to go in the larger sense.

Collision Magazine 119

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