ollision C
Volume 13 Issue 1
The International Compendium for Crash Research
Power Loss Issues
Related To Edr Data In Motorcycles
Unmanned Aircraft Systems Photogrammetry VS. Total Station
DAsh Camera
video velocity analysis Cover Pages.indd 1
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S I MON
SImulation MOdel Non-linear SIMON is a fully 3-dimensional dynamic simulation of the response of one or more vehicles to: • Driver Inputs (steering, braking, throttle, gear shift) • Collisions • Terrain Factors (irregular terrain, curbs, soft soil, slippery regions, hydroplaning, potholes, …) • Aerodynamics (wind forces, airborne trajectory) SIMON was built using the latest advances in software and simulation technology, based on a new, 3-D vehicle dynamics engine developed by Engineering Dynamics Corporation. Any number of vehicles may be included in a SIMON simulation. The user assigns initial positions and velocities for each vehicle. The user may also assign driver controls, wheel set-up conditions (tire blow-out, wheel damage, brake adjustment/failure, curb impact) and accelerometers. Using this information, SIMON calculates the forces acting on the vehicle and uses these forces to calculate vehicle position, velocity, acceleration and collision damage at user-specified time intervals. The results may be displayed numerically (in a spreadsheet format) or visually (in 3-D viewers). SIMON has been validated against numerous well-instrumented vehicle handling studies, including combined steering and braking, severe irregular terrain traversal, rollover tests, staged crash tests and tire blow-out experiments. Program results easily meet Federal standards for the admissibility of scientific evidence.
VISUAL REALITY
Cover Pages.indd 2
Engineering Dynamics Corporation • 8625 SW Cascade Ave. Suite 200 • Beaverton, OR 97008 USA • 888.768.6216 www.edccorp.com SIMON and DyMESH are trademarks of Engineering Dynamics Corporation. All rights reserved.
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Contents
Volume 13 Issue 1
inside 8
Crash-ol-o-gy
6
Letter From the Editor
5
Advertiser Index and Digital Download Information
48
features 10
Vehicle System Forensics for Crash Reconstruction by Wes Vandiver and Robert Anderson
16
Dash Camera Video Velocity Analysis by Adam Cybanski
38
Power Loss Issues Related To Edr Data In 2013-2017 Kawasaki Ninja 300 And Zx-6R Motorcycles by Edward C. Fatzinger Jr.
48
The Impact Of Nonlinear Boundary Geometry Considerations In Regards To Residual Damage Based Model Coefficients, Equivalent Barrier Speed And Internal Work Absorbed by Jai Singh
68
Small Unmanned Aircraft Systems Photogrammetry vs. Total Station by Joseph Weadon
86
My Turn at the Wheel: " Driver’s Early Arrival at the Scene Caused Accident?" by Erik Carlsson
88
Motorcycle Accident Reconstruction: Applicable Error Rates for Struck Vehicle EDR-Reported Delta-V by Nathan Rose, William Bortles, Neal Carter
112
Documenting A High Speed, Rear End, Partial Overlap, Crash Test Of A Large Sedan & Stationary Commercial Trailer by Craig Proctor-Parker www.collisionpumagazine.com
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88
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ADVERTISING RATES & INFO Crash Data Group Inc PO Box 892885, Temecula, CA 92589 Toll Free: 800-280-7940 E-mail: sbaker@crashdatagroup.com Web: www.collisionmagazine.com ISSN: 1934-8681
COLLISION STAFF Scott Baker Sean Haight Tonya Baker Courtney Baker
Owner, Managing Editor Senior Editor Advertising Manager Subscription Services
All rights reserved, © 2019 Cash Data Group Inc. 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. Dis-
senting 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 e-mail to the editor at sbaker@crashdatagroup.com or sending a "regular mail" letter to us at PO Box 892885, Temecula, CA 92589. By
sending correspondence to either our e-mail 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 e-mail 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 re-emerge, the existence of this publication and data disk in that universe cannot be guaranteed.
If you would like to advertise your products or services in Collision Magazine, rates, availability and other information are available online at: www.collisionmagazine.com
ADVERTISER INDEX
PAGE
4N6XPRT Systems Collision Magazine Collision Safety Institute Crash Academy Crash Data Group The Crash Hub Engineering Dynamics EDR Summit Houston Auto Appraisers Laser Technology Inc Leica Geosystems Northwestern CPS Tesla EDR Kit VirtualCRASH
Inside Back 4 61 46, 62 128, Back 110 Inside Front 47 62 37 2, 63-66 7 67 1
Included with this issue of Collision
is the 2019 EDR Summit presentation files (PDF). Use the link and password below to access the EDR Summit presentation files that were made available. Link: http://www.crashdatagroup.com/edr2019/ Password: 2019subaru
SUBMIT AN ARTICLE If you would like to submit an article to be published in Collision please review the following webpage for instructions: http://www.collisionmagazine.com/submit/
BACK ISSUES
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Next EDR Summit Houston, Texas March 9-11, 2020 www.edrsummit.com Collision Magazine - Volume 13 Issue 1 5
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crash
verb\'krash\ 1. to collide violently with an obstacle or another vehicle.
-ol·o·gy
noun\'äl-ə-jē\ 1. a subject of study; a branch of science. -ology is a back-formation from the names of certain disciplines. The -logy element basically means "the study of ____". Such words are formed from Greek or Latin roots with the terminal -logy derived from the Greek suffix -λογια (-logia), speaking, from λεγειν (legein), "to speak". Through the years -ology and -logy have come to mean, "study of" or "science of" and either of these suffixes often utilize the form of –ologist.
crash·ol·o·gy
noun\'krash-'äl-ə-jē \ 1. The science of crashes. So, Crashologists, welcome to Crashology – The Science of Crashes. In this new, recurring feature of Collision – The International Compendium for Crash Research, the authors plan to address a wide range of topics centered around the study of crashes and crash reconstruction. We plan to offer crash test reviews with a focus toward the validation of new or existing reconstruction methodologies and insight into the ever-increasing data we recover from vehicles. Original research and testing are planned in an effort to continue to broaden the information and data available to crash investigators and reconstructionists. Finally, there will be technical articles related to issues and concepts relevant to the collision reconstruction community. When someone describes a project as, “It’s a work in progress,” it is often with the intent of explaining why the current state of the project might look unfinished or not conform to other examples of similar work. We proudly consider this a “work in progress” because we recognize that the research in this field is never done and we have no existing model as our guide. We intend to offer topics of interest, always with the goal of pushing forward the science of crashes, which we now call, “Crashology.” The topic of the inaugural edition of Crashology is a recent development in the digital age of automobiles, Vehicle System Forensics for Crash Reconstruction.
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Vehicle System Forensics for Crash Reconstruction Wesley Vandiver collision forensics, inc
Robert Anderson Biomechanics analysis
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August 2017: In the early hours of the morning, several individuals get into an altercation at a bar. The incident moves outside to the streets where an 18-year-old throws a bottle, damaging the side-view mirror of a red Ford Mustang belonging to one of the antagonists. The 18-year-old flees with a companion on a moped. Meanwhile, the Mustang owner, in a rage, pursues them at high speed, until moments later the Mustang crashes into the moped from behind, leaving one rider dead, another severely injured, and a homicide case for detectives to investigate. There were differing stories from witnesses, gaps in the evidence gathered from closed circuit cameras, forensics from two vehicles and the crime scene itself. All left key questions about precisely what had happened during the chase. Prosecutors and police were pursuing a charge of “death by dangerous driving” instead of murder, based on the initial investigation by the Metropolitan Police Service in London. But a relatively new source of digital evidence—the data stored inside the vehicle systems —revealed that the driver of the Mustang was accelerating as his car approached and at the precise moment of impact with the moped. Additional data was found on the vehicle systems that showed deliberate actions taken by the driver of the vehicle to harm the riders of the moped, as well as pinpointing the precise route taken from the bar to the location of impact. With this new evidence in hand, the charge was elevated to murder…[1]
such as roadway markings, vehicle damage, and recorded data from event data recorders (EDRs). Digital forensics specialists routinely work with digital data from electronic devices, such as cell phones and computers. Digital forensics is the practice of preserving, gathering and presenting evidence from digital devices for the purposes of criminal or civil investigations. [5] Key evidence in the above case included both crash evidence and forensic data recovered from the vehicle’s infotainment and telematics system. Data acquired from these systems as well as others in the vehicle are rapidly growing sources of critical evidence. Crash investigators routinely acquire and analyze electronic data in their day-to-day investigations. The Crash Data Retrieval (CDR) system brought to market by Vetronix Corporation and subsequently acquired and expanded by Bosch Corporation has, for nearly two decades, been a valuable source of crash data for investigators. Over time, the available data from supported vehicles have grown from obtaining a partial, single-axis crash pulse to modern data that include a number of pre-crash parameters. The availability of EDR data brought crash investigators into the digital forensics world and introduced them to the processes of data acquisition and data analysis. A new and different source of automotive forensic data has emerged in recent years – infotainment/telematics system data. These data are acquired using the iVe system, developed by Berla Corporation, in Annapolis Maryland. [6] The iVe ecosystem is a collection of tools that consists of a mobile app used for identification and system removal, a hardware kit for data acquisition, and forensic software used for data analysis.
Figure 1. Crime scene photo courtesy Metropolitan Police The Metropolitan Police Service in London is one of the most technologically advanced law enforcement agencies in the world. This case required the cooperative efforts of investigators from multiple disciplines and the result was a successful murder prosecution. [2] [3] [4] Crash investigators are generally accustomed to working with evidence www.collisionpumagazine.com
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Figure 2. iVe Mobile Application
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DASH CAMERA VIDEO VELOCITY ANALYSIS Adam Cybanski Gyro Flight & Safety Analysis Inc.
O
verview On 20 June 2018, a vehicle performance engineer from the Office of Research and Engineering at the National Transportation Safety Board (NTSB) met with the founder of Gyro Flight & Safety Analysis in Ottawa, Canada. Dash camera refresher training was conducted and covered a variety of topics including frame extraction, frame rate calculation, lens distortion, focal length estimation, tracking, geoidentification and solving camera motion.
The author (Adam Cybanski) carried out live testing in the area. As part of a practical exercise, he drove down a stretch of road for speed testing. This was captured using a dash camera, and a racing quality GPS. An initial analysis of the dash camera footage was conducted during the refresher training. Comprehensive camera analysis followed over several months, and is now provided below in order to compare the velocities extracted from dash camera video, with the high-performance GPS data. 16 Collision Magazine - Volume 13 Issue 1
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Background
As an aircraft accident investigator, Adam Cybanski has been extracting velocity information from witness video since 2008. Cockpit cameras, similar to dash cameras, ramp cameras similar to traffic cameras, and handheld witness video were photogrammetrically analyzed in order to derive the velocities of the cameras, and the vehicles seen in the field of view as part of aircraft accident investigations. In 2015 the author also started assisting the local police with investigations of traffic accidents that were caught on video. The techniques developed for analyzing video of aircraft accidents are now employed for traffic accident reconstruction. Velocity analysis from witness video is based on three workflows: matchmoving, geoidentification and time-distance. Matchmoving is the calculation of camera and object position from video. Geoidentification involves identifying references from a video in real world coordinates (lat/long, UTM grid). Time-distance requires analysis of
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video frame timings and consolidation with distances to calculate speed.
camera correctly to match the actual camera that captured the original imagery.
Matchmoving is a process in film making which aims to insert computer graphics into live-action footage, with correct position, scale, orientation and motion relative to the background image. This has the effect of making the CGI content blend seamlessly into the live footage, but requires careful photogrammetric analysis of the video using special software. Analysis is used to determine exactly where the camera was in 3D space, what its orientation was, and the 3D location of any objects of interest.
The end result of geoidentification and matchmoving is typically position and distance information. Analysis of video can yield up to 30 measurements per second, and the timing between each measurement is not always constant. Using detailed analysis, a precise estimation on each image's time must be calculated, then combined with distance estimates to yield velocities. The resulting data then undergoes statistical techniques in order to produce derived plots of the velocities over time.
Geoidentification involves the designation of identifiable features in video, and determining measured coordinates for them based on their real-world location. Sources for this data are typically surveys made onsite, but resources such as Google Earth can be used in their place. The aim of this information is to help the software determine the scale of the scene under analysis, and the relative location of the identifiable features so that it can orient a virtual
Speed Testing
Speed testing was conducted in Ottawa. A vehicle was fitted with two GPS receivers and a dash camera. The author drove down a nearby road at different speeds. The intent was to compare speeds derived from video velocity analysis of the dash cameras with truth data from the GPS receivers.
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POWER LOSS ISSUES RELATED TO EDR DATA IN 2013-2017 KAWASAKI NINJA 300 AND ZX-6R MOTORCYCLES Edward C. Fatzinger Jr., MS, PE
Momentum Engineering Corp.
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S
tarting in 2013 Kawasaki Heavy Industries, Ltd. (KHI) has installed Event Data Recorders (EDR) on select US sold motorcycles. The two motorcycles covered in 2013 are the Ninja 300 and the ZX-6R. On both these models an EDR event is triggered when the motorcycle is tipped over and goes into an emergency shutdown (ES). The emergency shutdown is a safety feature that involves shutting off the fuel pump relay, fuel injectors, and ignition system when the motorcycle senses it has fallen. The rest of the electronics will remain active. Additionally, to trigger an EDR event the rear wheel must be in motion or gone through a sudden deceleration in the several seconds prior to ES. On the Ninja 300 and ZX-6R the time between tip-over and ES is approximately 1.3 seconds. However, as studies have shown this time can be significantly increased if the motorcycle is still sliding/bouncing creating considerable “noise” in the tip-over sensor. The data parameters captured in an EDR event can be seen in Table 1. In addition to the data parameters, the EDR will capture the ECU runtime and key cycles at the event, as well as the elapsed ECU runtime and key cycles since the event. 1,2 2 Hz data Front wheel speed* Rear wheel speed Gear Position Inlet Air Temperature Coolant Temperature Battery Voltage DTC’s Power (P-Mode)* KTRC Mode*
10 Hz data Throttle Position Engine RPM Clutch In/Out Fuel Injector Pulse Timing BTDC Fuel Cutout *ZX-6R only
Table 1: EDR data parameters for Ninja 300 and ZX-6R The EDR data is stored in the Engine Control Unit (ECU) on three non-volatile memory chips (EEPROMs). An image of the three EEPROMs on the Ninja 300 can be seen in Figure 1. The power supply critical to triggering and subsequently writing an EDR event to the ECU comes in two forms; switched and unswitched. The switched power comes from the ECU relay and the unswitched power comes straight from the battery. Similar to your typical automotive radio, there is a constant power feed (unswitched) which stores the clock, presets, and other user data on the radio, and a switched power feed that generally powers up the radio. The ECUs in the Ninja 300 and ZX-6R work in a very similar fashion. Both the switched and unswitched power to the ECU is necessary for the motorcycle to go into ES and trigger an EDR event. Once in ES and the EDR event is triggered, only the unswitched power is necessary to save the data to the EEPROMs. On the Ninja 300, all the motorcycle power comes through the main fuse located on the starter relay assembly (see Figure 2). From the main fuse, unswitched power is fed directly to the ECU through the fuel injection fuse. Additionally, power is fed directly to the ignition switch from the main fuse. When energized, the ignition switch powers the switched side of the fuse block. This switched side of the fuse block is responsible for energizing the ECU relay. Unfortunately, if the main fuse of the Ninja 300 is compromised, the ECU will lose both the switched and unswitched power assuming the engine has stalled. However, if the main fuse is blown or there is a sudden battery loss and the engine has not stalled, the motorcycle’s alternator power will keep the engine running and supply the switched and unswitched power to the ECU. www.collisionpumagazine.com
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The impact of nonlinear boundary
geometry considerations in regards to residual damage based model coefficients, equivalent barrier speed and internal work absorbed Jai Singh, BS, MS, MA, ACTAR Biomechanical Engineering Analysis & Research, Inc.
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A
bstract Extant closed-form analytic solutions for quantifying residual damage based model parameters, equivalent barrier speed (EBS) and internal work absorbed (IWA) that use the residual damage profile present after a collision are predicated upon the employment of global or piecewise linear interpolation at the level of the residual damage profile. The subject work focuses, primarily, on the theoretical evaluation of this predicate. This evaluation is approached first by defining the residual damage depth function as the difference between the reference and damaged boundary geometry functions. It is shown that the extant formulation is reproducible when both boundary geometry functions are separately linear (interpolated or otherwise) over a mutual domain. It is also shown that the presence of non-linearity in either boundary geometry function also appears in the residual damage depth function and thereby changes the form of the equations that are currently employed for determining the relevant parameters. The case in which the interpolation function for the reference boundary geometry consists of a general polynomial function is detailed in depth. A worked example is provided in which other forms of interpolation functions are considered for both the reference and damaged boundary geometries.
I
ntroduction Equations (1-2) are the most commonly employed mathematical relationships that serve as foundational for the determination of collision severity as a function of the residual damage present to a motor vehicle following involvement in an impact (Sharma et al., 2007). The first of these equations, proposed by Campbell (1972, 1974), is an empirical relationship between the depth of residual damage (c) and the equivalent barrier speed (EBS). The second equation, proposed by McHenry (1976), relates the residual damage depth to the peak collision force magnitude, |F|, normalized to the reference configuration direct damage contact width (L) and is one of the critical relationships in the third iteration of the Calspan Reconstruction of Accident Speeds on the Highway (CRASH3) damage analysis algorithm. This relationship is analytic for the closure phase of a coaxial collision when the structural response characteristics of the collision partners are modeled as linear elastic (Noga and Oppenheim, 1983) but becomes empirical in consider-
ation of collisions with a separation phase for which the coefficient of restitution is not zero-valued. EBS = b0 + b1c F L−1 = A + Bc
(2)
The internal work absorbed (IWA) during a collision can be directly related to the EBS and the mass of the collision partner (m) as shown by equation (3). IWA =
1 mEBS2 2
(3)
The relationship shown by equation (2) is not a timeparametric force-deflection response nor does it represent a time-parametric force-deflection response shifted along the abscissa. The force-deflection data generated from any singular collision test, for example, maps to a single point along the response curve. In practice, however, this relationship is treated as being equivalent to a time-parametric force-deflection response in regards to the determination of the IWA. Traditional solution for IWA for uneven damage profiles In the consideration of residual damage profiles for which the depth of residual damage varies as a function of location along the width of the direct damage portion of the profile, the traditional approach has been that of using a discretization scheme consisting of the piecewise employment of the trapezoidal rule using two, four or six equally spaced nodal points. This was extended to the use of any N number of equally spaced nodal points (Singh et al., 2003) and then for the use of any N number of unequally spaced nodal points (Singh, 2005a). The latter presentation, being the most general, is considered herein. In this regard, the independent variable, l {l: 0 ≤ l ≤ L}, denoting the location along the width of the direct damage portion of the residual damage profile, in the plan view and mapped to the reference configuration, is introduced. The residual damage depth function may then be stated as c(l). The ith {i: 1 ≤ i ≤ N} nodal value of the residual damage depth, located at li, is denoted as ci. The linear interpolation function between successive nodal values derives from the simple definition of a two-dimensional line.
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TE
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1
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Small Unmanned Aircraft Systems Photogrammetry vs. Total Station Sergeant Joseph Weadon, III Missouri State Highway Patrol
I
M
ntroduction The use of small unmanned aircraft systems (sUAS) for crash scene mapping has taken the reconstruction community by storm. Many crash reconstructionists have begun using these aerial photography platforms in conjunction with photogrammetry software to capture scene evidence and roadway characteristics. Most, it seems, have relied on what they were told about the accuracy of the process in a short course and simply accepted its validity. We took a different approach. To determine the validity of the data and any potential error rate, we compared our results to another long-accepted method of measurement; the total station.
ethodology The testing took place at the Emergency Vehicle Operations Course (EVOC) of the Missouri State Highway Patrol, located in Jefferson City, Missouri. We selected four sites along the course, which provided varying degrees of grade and super-elevation. Additionally, the sites were composed of a variety of surfaces. After the sites were identified, a total of 100 test points were painted on the different surfaces at each site. Test points were painted using a template comprised of offset 0.3-foot squares, which touched only at one corner. White paint was used to paint most test points and all points were numbered. Figure 1: Test Points shows a sample of the test points painted on asphalt and grass. 68 Collision Magazine - Volume 13 Issue 1
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Site one was exclusively asphalt. It was a large, banked curve with extreme super-elevation. The site was approximately 900 feet long. Site two was in an “S” shaped curve, had a change in grade, and incorporated a negative super-elevation. It was approximately 550 feet long. Of the 100 test points at site two, 64 were on asphalt and 36 were on grass. The grass was approximately 0.2-0.3 feet tall. Site three was mostly level and was approximately 450 feet long. There was a 0.35-foot curb on the asphalt that paralleled the roadway. At site three, 70 points were painted on asphalt and 30 points were painted on the varying height grass surface. The grass ranged from 0.2 feet tall to over 2.5 feet tall. Furrows were created in the taller grass using a string trimmer(weed-eater) and test points were painted on the ground in the furrows. Site four was approximately 700 feet long and consisted of both asphalt and gravel roadway. The asphalt road was
The sUAS used for this testing was a DJI Inspire 2 with a Zenmuse X4S camera. Each site was photographed in two separate ways. The first photographs were taken with the camera looking straight down at a 90-degree angle to the surface (ortho mode). The second group of photos were taken with the camera gimbal slightly angled (oblique mode). The oblique mode angle varied site to site but was between approximately 75 degrees and 90 degrees. This simulated flying a crash scene with moving traffic on the road without flying directly over the traffic. Existing federal regulations prohibit flying a sUAS above moving traffic. For each mode used, the following guidelines were adopted. One pass was flown at approximately 100 feet above ground level (AGL). During this pass, photographs were taken with an overlap of approximately 80 percent. During this pass, each point along the test site should have shown up in
After documenting each site with the total station it was flown and photographed with a sUAS. mostly level. The gravel sloped down away from the asphalt. The gravel area was approximately the width of a one lane road. At site four, 80 test points were painted on the asphalt surface and 20 points were painted on the gravel. In addition to the test points, ground control points (GCPs) were painted at each site. The ground control points were painted at each end of the test points and throughout the center. Site three, which had the “furrows” in the tall grass, had ground control points painted in the furrows and grass. Each site was mapped with a Sokkia iX robotic total station, using Magnet Field as the data collection software. To mitigate pole sway, the range pole was held by one person and the data collector was held by another. When the test points were documented, the total station averaged three shots to improve its accuracy. After the 100 test points were documented, the ground control points were documented. After documenting each site with the total station, it was flown and photographed with a sUAS.
approximately five photographs. The second pass was flown at approximately 50 feet AGL. During this pass photographs were taken with an overlap of approximately 75 percent. This means each point should have shown up in approximately four photographs. During this pass if the entire width of the test area was not able to be seen, then two passes were flown at 50 feet and they overlapped in the center of the test area. The last pass was flown at approximately 25 feet AGL. During this pass there should have been 50 percent overlap of each photograph. This means each point should have shown up in approximately two photographs. Again, if the width of the test site cannot be seen in each photograph, then the photographs were overlapped near the center of the test site and two or more passes were flown. The only difference in the oblique passes was the sUAS was not flown over the “lanes of travel.”
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eel h W The t a rn u T My
Driver’s Early Arrival at the Scene Caused Accident? Erik Carlsson
T
his is a short story, with no pictures or illustrations, but I believe it is nevertheless offering very interesting reading for anyone who works with attorneys or insurance companies with the purpose of determining the cause of traffic accidents. A car driver on his way to an assignment traveled westbound on Interstate 80 in New Jersey. He turned off the highway onto an exit ramp on his right that led up to a two-way north/south local street that passed over the highway. There was no traffic approaching from the left at the end of the ramp, so the driver made a right turn and continued north. About 200 yards north of the intersection is a restaurant on the eastern side of the street. Just as the driver passed the entrance driveway to the restaurant, the driver of a southbound car who was on his way to the restaurant started his left turn, and his car collided with the northbound car.
The accident reconstruction firm presented a detailed report of the accident and the damage to the vehicles, and posited that the plaintiff was the sole cause of the accident. Had he passed the restaurant’s driveway a few seconds later, the defendant’s car would have entered the driveway before the plaintiff’s car reached the scene!
What I said above may sound like bad joke, but it is the opinion presented by the accident reconstruction firm in its report. As expected, the writer of the report explained his reason for his opinion. The defendant was meeting a friend of his at the restaurant when the accident happened. The friend arrived a few minutes before the defendant and had stepped out of his car. He was looking on the road, expecting to see his friend arriving, and saw the collision. But he had also been looking the other way and had seen the plaintiff’s car coming up the exit ramp from the highway. He saw, he testified, that the plaintiff had a red light at the end The left-turning driver stated at the police investiga- of the exit ramp, and he saw that the plaintiff made tion that followed that he didn’t see the oncoming his turn to the right without stopping. In its report, car because he was looking to his left, focusing on the the accident reconstruction firm considered that statedriveway that led into the restaurant’s parking lot. The ment by the defendant’s friend as evidence that the northbound driver stated that he was merely traveling plaintiff violated a New Jersey regulation that states down the straight road when the driver of the oncom- that a driver may not make a right turn on red without ing car suddenly started to turn left, causing the cars first stopping the vehicle. Thus, the expert opined, had to collide. the plaintiff not violated that regulation, but made a The northbound driver naturally was rather upset, and full stop before entering the street, he would have arsubsequently sued the turning driver, claiming inju- rived at the scene a few seconds later, and this would ries, lost wages, reduced value of his new car, etc. The have been enough for the defendant to complete his defendant, or rather his attorney, retained an accident left turn onto the restaurant’s driveway ahead of the reconstruction firm that I believe had been recom- approaching car. Therefore, the plaintiff was the sole cause of the accident. mended by the defendant’s car insurance company.
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Some thoughts: Not surprisingly, the case did not go to court, but the parties settled the case. One may wonder, though, would the attorney for the defendant really have been prepared to try the case in court? Would the defense expert have been prepared to tell a jury or a judge that the plaintiff caused the collision because he arrived at the scene a few seconds “too early”, while the defendant, who made a left turn on a two-way road without even looking forward, was not the one who caused the accident, but merely an innocent victim?
he began his right turn, which of course is what he could be expected to say.) One can make more “what if ” questions. What if the plaintiff had arrived at the intersection a few seconds earlier and made a full stop and then started? He may then have arrived at the scene of the accident at the very same moment as he now did? Or what if a northbound car had passed the intersection with the exit ramp just before the plaintiff made his right turn? That car may have arrived at the accident scene at the moment the defendant began his left turn and could have been the car that collided with the defendant’s car.
After all, it is very common that drivers make a right turn on red without stopping completely. Furthermore, could the defendant’s friend really have seen that the plaintiff had a red light some 200 yards Anyone who has some thought about this case is away considering that the traffic signal was at about welcome to contact me at erikcarlsson@live.com. 90 degrees angle from the witness’ position? (The plaintiff claimed that the light turned green just as
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Motorcycle Accident Reconstruction:
Applicable Error Rates for Struck Vehicle EDR-Reported Delta-V Nathan Rose William Bortles Neal Carter
I
ntroduction A common motorcycle crash scenario occurs when a passenger vehicle equipped with an Event Data Recorder (EDR) turns left across the path of a motorcycle and is struck by the motorcycle. The EDR data on the passenger vehicle will often be accessible with either the Bosch Crash Data Retrieval (CDR) system or the Global Information Technology (GIT) system. In these instances, pre-crash EDR data can be useful for establishing the specific characteristics of the left turn that preceded the collision. This data may include speed, throttle or accelerator pedal percentage, brake applications, and steering angles for the struck vehicle. In addition to that, an EDR-reported change in velocity (∆V) from the struck vehicle can potentially be used to infer the ∆V and impact speed of the motorcycle. This article reviews and summarizes the literature related to error rates for EDR-reported ∆Vs under various impact conditions and assesses which of these error rates are most applicable when analyzing impacts between motorcycles and passenger vehicles. This lays the groundwork for the companion article [Rose, 2019], which illustrates the application of these error rates within the context of reconstructing real-world intersection collisions involving motorcycles and EDR-equipped passenger vehicles. The companion article also covers the accuracy and application of the pre-crash data from the struck vehicle to these collisions. This article focuses only on the ∆V. There are potential problems that can arise when using the struck vehicle ∆V to infer the ∆V and impact speed of the motorcycle, particularly related to the large weight ratio that often exists between the motorcycle and the struck vehicle. Newton’s 2nd and 3rd laws together (conservation of momentum) dictate that, during a collision between two vehicles, the ratio of the mass of Vehicle #1 (m1) to the mass of Vehicle #2 (m2) is equal to the ratio of the change in velocity experienced by Vehicle #2 (∆V2) to the change in velocity experienced by Vehicle #1 (∆V1), as follows:
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Introducing The Crash Hub
The Crash Hub is a new vehicle crash expert directory site. Both the ARC Network and EDR Experts have been merged into a single site giving the end user the ability to search, review, and retain vehicle crash experts around the world. The Crash Hub is also much more than an expert directory site because each member of The Crash Hub has the ability to add meaningful content to the site in the form of articles, events, training classes, photo albums, and videos. The Crash Hub can also be used as job search site and a classified ads directory. The Crash Hub is also the place to search, review and learn about products available to the vehicle crash investigator.
To learn more, visit at www.thecrashhub.com
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Search Engine
The Crash Hub has a powerful search engine allowing you to locate experts around the world with a simple click of your mouse. You can search by expertise, location, name, or any keyword.
Search Results
The Crash Hub search results profile the globe and pin the location of every active member. Simply move your mouse over the pin and that expert will be displayed. The results map has full “zoom” capabilities to zero in on the location you are looking for.
Member Dashboard
Each member has full access and control of their professional profile in The Crash Hub. Add your photo, company logo, C.V., full contact information, specialties, publish articles, post events, job listings, photo albums, videos, and even post classified ads. You can even check how many people have viewed your professional profile.
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Documenting A High Speed, Rear End, Partial Overlap, Crash Test Of A Large Sedan & Stationary Commercial Trailer Craig Proctor-Parker
Accident Specialist, Durban, South Africa
A
bstract Crash scenarios involving a rear end impact are common place internationally. Some of the most devastating are often where a sedan collides into the rear of a commercial trailer, partial overlap. This type of crash is almost always with serious or fatal consequences. With a high number of these identified in a recent high profile Major Crash Investigation (MCI) project, a real life high speed test of this scenario was undertaken. Obtaining data from such a crash in a controlled environment for future comparative analysis is rarely presented. This paper presents a brief overview of the setup and results of the high speed rear end, sedan to stationary commercial trailer.
Keywords & phrases - Rear-end crash; head-rear crash; Under- ride crash, Rear end accident, High speed rear end impact, Partial overlap impact.
I
ntroduction: This research is based on a practical crash test session undertaken by Accident Specialist as a combination of research and awareness. Three different crash scenarios were presented, two of these remote controlled1. This particular crash being one of the three and is available online at: https://www.youtube.com/watch?v=dsT1VCL18Uk
Internationally, rear end crash scenarios are well represented in crash statistics, this too is a statistic that is prevalent in South Africa. Such crash scenarios are typically as a direct result of major traffic congestion, vehicles broken down at hazardous locations and/or simply due to driver error in their negligence either as the vehicle being struck (Target), or the vehicle striking (Bullet). As with opposite 112 Collision Magazine - Volume 13 Issue 1
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direction head-on, type impacts, high speed rear end partial overlap impacts present an even greater risk for a number of reason, not least of all the reduced contact area and therefore reduction in available material to absorb and dissipate the energies. Such crash scenarios typically result in fatal or at least serious injuries and damages. The investigation of such a crash scenario almost always centres around certain interrelated key issues that are almost always raised in litigation 35, an issue that will be highlighted later in the paper, however in brief are typically: •
Where was the target vehicle • •
Precise point of impact
It`s lateral position in respect of the road layout
•
Why was the Target vehicle at that position
•
What was pre-crash visibility
•
What was the speed of the vehicles
•
Mechanical issues?
•
The line of sight of the Bullet vehicle
•
Usually the focus is on the Bullet vehicle, but may also be the Target vehicle.
The nature of a high speed, partial overlap rear end crash is such that massive destruction of the Bullet vehicle is typical. This is especially so where massive disparity between the general structure types, size and strengths are the case as where a sedan strikes a commercial vehicle. Such disparities are already well identified internationally 13,14,15. If not from the crash itself, the extent of decimation to the Bullet vehicle
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is typically aggravated by further rescue cutting and recovery process. These damages all too often contaminate the original damages and on occasion, telemetry that may have been available 12. On occasion, conflagration results and too, decimates vital evidential factors. There is no doubt that in time, with advancement in technology, detailed telemetry will be and is already to some extent available, be secure and easily downloadable from vehicles post-crash. It may be that such data is streamed live time and stored off-site of the vehicles 12,37a,37b. Nonetheless, there will almost always be some need to do a physical inspection and consideration of certain parameters of a crash. The contributions of this paper are: •
Identify the characteristic correlation with the results of the vehicles after a crash of this manner
• • • •
Identify possible weaknesses on the Bullet and the Target that could be improved
Identify common evidence after such a crash has occurred
Determine to what extent resulting evidence can be used to answer some of the many questions that arise from this type of crash Provide documented record of the specific crash for further analysis if and when required
L
iterature review & research: The subject matter of rear end impacts is a relatively well researched well documented one 3,4,6,8,17 et al.. Rear end crash scenarios in general are extremely prevalent and in the USA during 1999 they accounted for nearly one third of all crashes 7. During 2000 they once again accounted for as much as 29.7% of all crash cases 2.
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Get the facts of the crash get answers quickly
Helping you understand the crash evaluate causation
validate physical evidence
corroborate witness statements
With proven admissibility in court, the Bosch CDR Tool is the worldwide standard used by law enforcement for obtaining unbiased, critical crash data from vehicles. Equip your investigators with the trusted tool to get answers quickly, evaluate causation & physical evidence and corroborate witness statements producing accurate incident reports. In addition to selling the Bosch CDR Tool, Crash Data Group also assists with training needs, assuring you understand how to use the tool properly. The CDR Tool allows you access to crash data from the majority of vehicles on the road today. Because of the impact the data provides to the investigation process, this tool has become the essential tool for law enforcement and accident inviestigators.
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