Volume 17, Issue 1 by Collision Publishing

ollision C

Volume 17 Issue 1

The International Compendium for Crash Research

Using Centrodes

CATAIR 2022

to Describe Vehicle

Crash Conference

Motion

Crashology Crash Analysis with Berla and EDR Data,

Trigger counts marked “Invalid” in Toyota EDR data

Two Case Studies

Moving Masses and Barrier Impact Dynamics

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Collision Magazine - Volume 17 Issue 1 1

Publisher's Message It’s finally here, Volume 17, Issue 1 of Collision! Over the last few months, there were times I wondered if we’d get here, but we got it together AND we have Vol 17, Issue 2 almost ready to go in a just a couple short months. When I took the reigns at Collision Publishing in March this year, I looked at all the Scott Baker had accomplished with Collision and the EDR Summit and wondered if I could pull off anything close to what he had done so successfully for so long.

Well, the jury’s still out on that and it’s taken a lot of work and the time and patience of a lot of people and a learning curve was far steeper than I expected to get to this point but we did it. Now the goal is to get Issue 2 out in time for the EDR Summit and then Volume 18 on track to fill out 2024 mid-year.

other conference later in 2024 outside of Houston. We’ll have to see… In the meantime, the EDR Summit returns for 2024 in Houston at the Sheraton – not the Hilton – and the speakers and topics are set. Exciting new research on a correlation between cell phone date and time and vehicle data – EDR and GM’s FCM, for example – date and time should be one of the highlights.

Either write something worth reading. or do something worth writing.

Don Floyd from GM, Bill Rose from Bosch as well as other new presenters and relevant topics will make the 2024 Summit a “don’t miss” opportunity not the “same ol’, same ol’.”

- Benjamin Franklin.

Benjamin Franklin once said “Either write something worth reading, or do something worth writing [about].” I’d like to think that’s the idea behind Collision Magazine. We have a group of great frequently contributing authors and want to continue to live up to the idea that Collision will be the home of new and fresh, articles, papers, and relevant information.

For the Summit return there’s an optional session after the Summit from a long-time Toyota in-house trainer on how to read and use Toyota Techstream data more effectively. This hands-on session is a first for the EDR Summit and is sure to be a hit – not to be missed. I look forward to reaching out to you through the coming Volume of Collision Magazine and meeting you all at the 2024 Summit.

In the coming few months we have the EDR Summit (February 2024) and the second issue in Volume 17 of Collision and some other exciting ideas in development. There’s talk of perhaps an-

Rakel Arnardttir - Publisher & Graphic Designer 2

Collision Magazine - Volume 17 Issue 1

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In this issue 2

Volume 17, Issue 1

Publisher's Message 16

Collision Magazine Info and Advertiser Index

Crash·ol·o·gy -Crash Analysis with Berla and EDR Data, Two Case Studies by Wesley Vandiver, Robert Anderson, Michelle Hoffman, David Hallman, Billy Cox

Using Centrodes to Describe Vehicle Motion

by Micky Marine, SSi Phoenix, Inc.

Performance of BMW Event Data Recorder (EDR) in Instrumented Barrier and Vehicle-to-Vehicle Crashes by Robert D. Anderson, Biomechanics Analysis and Michael Rosenfield, RSR Engineering

Personally Identifying Information

by Katarina Juric

Trigger counts marked “Invalid” in Toyota EDR data - Part 1 by W. R. "Rusty" Haight, Collision Safety Institute

What Is Tesla Sentry Mode And How Does It Work? by Rehan Arif

102 84

Moving Masses and Barrier Impact Dynamics by Micky Marine, SSi Phoenix, Inc.

102 CATAIR 2022 Crash Conference by Michael Rosenfield RSR Engineering, and Robert D. Anderson Biomechanics Analysis

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COLLISION STAFF Rakel Arnardottir Sean Haight W. R. Rusty Haight

Publisher Senior Editor Editorial Cordinator

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https://issuu.com/collisionpublishing All rights reserved, ©2023 Collision Publishing, LLC. The opinions and conclusions expressed in this publication and in any associated data and content of 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. 4

Collision Magazine - Volume 17 Issue 1

PAGE

4N6XPRT

Inside Front Cover

Aperture

1, 115

Alterra

Crash Data Group 15, Inside Back Cover EDR Summit

42, 48-49

Crash Hub

Car Clouds

CSI

101

Skillwise

116

Eng. Dynamics

Back Cover

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Collision Magazine - Volume 17 Issue 1 5

crash·ol·o·gy THE SCIENCE OF CRASHES Wesley Vandiver

Robert Anderson

Collision Forensics

Michelle Hoffman Forensic Injury Analysis

Biomechanics Analysis

David Hallman Hallman Engineering

Billy Cox

Billy Cox Group

Crash Analysis with Berla and EDR Data, Two Case Studies

Most vehicles on the road today are equipped with airbag control modules (ACMs), which store crash (EDR) data that can be retrieved and utilized to assist in reconstructing a crash. For the collision reconstructionist, the ability to retrieve digital evidence of vehicle speed and driver’s actions around the time of a particular incident can yield key evidence in an investigation. The acquisition of vehicle speed data from Event Data Recorders (EDRs) has become commonplace and is a routine item on the checklist for those investigating vehicular incidents. Much has been written about the accuracy of EDR data from a multitude of vehicle tests involving actual crashes, simulated crashes, hard acceleration, hard braking, etc. In summary, nearly all experts agree that EDR data is tremendously valuable but should always be considered alongside the other physical evidence and a proper analysis of that evidence as part of a situationally complete reconstruction. More and more vehicles are also equipped with multiple other modules which store data that can be retrieved and used for crash and / or other analysis of driver actions prior to and even after a crash. More recently available to the reconstructionist than EDR data is Vehicle System data acquired using Berla iVe. As will be demonstrated through two case studies, the additional data acquired using Berla iVe can be used to analyze driver behavior before, during, and after an incident; identify time, date, and place of an incident; as well as identify cellular phones connected to the vehicle. This article will present two case studies of vehicles which had both EDR data from a crash as well as data that was 6

Collision Magazine - Volume 17 Issue 1

retrieved from the infotainment system using the Berla iVe hardware and software. Having both Berla and EDR data sets allowed comparison between the two, to evaluate and confirm that the data from the two separate systems agreed. Case 1 – 2020 Ford F150 The first case involves a 2020 Ford F150 (Figures 1 and 2) which was reportedly stolen, involved in a hit and run crash, and then abandoned. The owner reported that the vehicle had been stolen from their driveway earlier in the evening and that they were unaware it was missing until the police called them to report it had been recovered. The F150 contained a Ford Sync system, Generation 3, Version 2 which was removed and imaged with the Berla iVe hardware and software. The EDR data was imaged with the Bosch Crash Data Retrieval (CDR) Tool equipment and software. The data from the infotainment system was analyzed and a map (Figure 3) and a timeline of events beginning at 7:04 pm on 7/22/2021 and ending on 7/23/2021 at approximately 1:40 am was prepared and is shown: 7/22/2021 – 7:04 pm (Track 24) The subject vehicle starts at 5108 Brookdale Drive N.

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A Galaxy S20 Ultra 5G phone connects, carrier is TMobile, number: 1-763-614-XXXX

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A Galaxy S20 Ultra 5G phone connects, T-Mobile, number: 1-763-614-XXXX

•

7/22/2021 – 10:58 pm (Track 29)

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The subject vehicle arrives near 1650 White Bear Avenue in St. Paul MN

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7/22/2021 – 11:45 pm (Track 31)

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The subject vehicle starts near 1650 White Bear Avenue

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A Galaxy S20 Ultra 5G phone connects, T-Mobile, number: 1-763-614-XXXX (11:47 pm)

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7/22/2021 – 11:49 pm (Track 31)

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The subject vehicle stops near 1800 White Bear Avenue but is not shut off.

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7/22/2021 – 11:50 pm (Track 31)

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The subject vehicle leaves the area of 1800 White Bear Avenue.

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7/22/2021 – 11:53 pm (Track 31)

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Crash detected at the intersection of White Bear Avenue and Highway 36, specifically in the intersection that leads to the entrance to westbound Highway 36.

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The subject vehicle does not stop at the time of the crash.

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7/22/2021 – 11:56 pm (Track 31)

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Vehicle stops on the shoulder of Highway 36 just west of White Bear Avenue entrance.

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Driver’s door is closed.

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A Galaxy S20 Ultra 5G phone becomes unavailable, T-Mobile, number: 1-763-614-XXXX

Figure 1: 2020 Ford F150

Figure 2: 2020 Ford F150 •

7/22/2021 – 7:40 pm (Track 24)

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The subject vehicle arrives near 1930 Buerkle Road in White Bear Lake MN

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7/22/2021 – 9:04 pm (Track 26)

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The subject vehicle starts near Buerkle Road

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7/22/2021 – 9:14 pm (Track 26)

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7/23/2021 – 12:07 am (Track 31)

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A Galaxy S20 Ultra 5G phone connects, T-Mobile, number: 1-763-614-XXXX

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Track 31 ends.

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7/22/2021 – 9:16 pm (Track 26)

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7/23/2021 – 12:29 am

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The subject vehicle arrives near 1800 White Bear Avenue in Maplewood MN

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Door opens, vehicle wakes up – Highway 36 shoulder.

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7/22/2021 – 10:53 pm (Track 29)

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7/23/2021 – 1:39 am

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The subject vehicle starts near 1800 White Bear Avenue

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Door opens and closes – Twin City Towing impound lot.

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Collision Magazine Volume17 17 Issue 1 7 Collision Magazine - -Volume

Figure 14: Paying particular attention to the last second of pre-crash data (Figure 14), the vehicle was decelerating until 0.4 seconds prior to AE and slows to about 3.3 mph

These are two examples of how Berla iVe acquired data and EDR data are complimentary and once aligned, pro-

vide a more comprehensive understanding of a crash than would have been available with either data-set alone.

Wilton “Wilt” Nelson 9 Dec 2927 - 13 Sept 2023 It's always hard to have to announce the passing of a colleague, especially someone as well known and admired as Wilt Nelson. Wilt passed on September 13, 2023 and was laid to rest at the Bushnell National Cemetery in Bushnell, FL. He is survived by Marion, his wife of 44 years, as well as two daughters Holly and Elizabeth, 4 grandchildren, and 11 great grandchildren. Wilt’s life seemed to be ordained into traffic safety after being run over as a child and sustaining two fractured femurs. Most of us remember him from his time at General Motors where he worked for 31 years as well as his time on various committees with the Society of Automotive Engineers. While at GM he worked at the Proving Grounds and was involved in numerous projects including experimental engineering and served as the Chief Investigator for the GM “Air Cushion Program” (predecessor to the “airbasystem”), “Automatic Belt Program,” and field crash studies and product evaluation. After retirement from GM, Wilt was a widely respected consultant operating as Crash Analysis & Reconstruction. Wilt was a founding member of the Midwest Association of Traffic Accident Investigators (MATAI) and worked tirelessly to improve crash investigation training and assist law enforcement with crash analysis in Michigan and throughout the Midwest. An avid Scuba diver, Wilt traveled the world after retirement on dive charters and found his way to dive spots and dive trips literally spanning the 7 seas not to mention the innumerable lakes and rivers worldwide. Wilt’s last email to his many correspondents began: “Dear friends, fellow countrymen and relatives…” and it those of us who will keep him in our hearts and minds. 14

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Using Centrodes to Describe Vehicle Motion Micky Marine SSi Phoenix, Inc.

n the study of rigid body kinematics, angular velocity is considered a property of the body and is not dependent on the choice of reference point selection. Meaning, for instance, angular rate sensors can be placed anywhere on a rigid body that undergoes rotational motion and the sensors will measure the angular velocity of that body. The angular velocity vector is therefore known as a free vector – its magnitude and direction can be specified, but its point of origin cannot. This fact then leads us to the notion of an instantaneous center of rotation (IC) where the velocity of any point on a rigid body can be defined solely by the angular velocity and the position vector between the IC and the point on the body. For general rigid body motion, the IC will change position over time leading to the concept that the motion of a rigid body can be described by a locus of ICs that form what are known as body and space centrodes. The objective of this article is to examine automobile motion in a variety of situations through the perspective of the centrodes concept. Examples for vehicle motion in the yaw, pitch and roll planes are presented, providing analysts with an uncommon but, hopefully, interesting perspective of rigid-body motion.

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Instantaneous Centers of Rotation & Centrodes In the context of automobile accident analysis, vehicle motion is very often considered planar. More than a few accidents occur with the vehicle(s) moving along on their tires and wheels, remaining in that condition throughout the accident. This is often referred to yaw-plane motion. Rollover accidents, on the other hand, can comprise complex three-dimensional motion, though frequently the predominant rotational motion is about the vehicle longitudinal axis. The vehicle is thus visualized in cross-section (a lamina of the vehicle) and the angular motion is considered to be about an axis that is perpendicular to the lamina. The IC is a point in the plane of interest that can be geometrically located at the intersection of lines that are drawn from any two points on a given body and are perpendicular to the absolute velocity vector at those respective points (see Figure 1 below). At a particular instant in time, the motion of the body can be thought of as being in pure rotation about the IC. The velocity of any point on the body, in either a space-fixed or a body-fixed reference frame, can be determined through the cross-product of the angular velocity vector and the position vector from the IC to the point of interest.

relative to that body while the space centrode is a virtual space-fixed terrain upon which the body centrode “rolls” without slipping. While we’ll confine ourselves to planar motion in this article, the centrodes concept can be expanded to the description of three-dimensional rigid body precession motion relative to an instantaneous axis of rotation where a virtual body cone rolls without slipping on a virtual space cone. References 1 and 2 both provide useful IC discussions. A simple example of a planar body and space centrode system is that of a wheel rolling over a flat surface in the absence of wheel slip (no sliding of the wheel along the surface plane). In this situation, as is commonly understood, the absolute velocity of the wheel at the point where it is in contact with the flat surface is zero. Thus, the IC is located at the wheel/surface contact point. At each successive instant, as the wheel rolls along the surface a new point on the wheel perimeter, now arriving at the surface, becomes the current IC. In this system, the body centrode is a circle that coincides with the wheel perimeter, while the space centrode is a line that coincides with the surface that the wheel is rolling on (Figure 2). Hence, the body centrode (wheel perimeter) is literally rolling on the space centrode (surface plane).

Figure 2: Body and Space Centrodes for a Wheel Rolling with No Slip

Figure 1: Construction of an Instantaneous Center of Rotation If the velocity time-history at some point on the vehicle and the angular velocity time-history of the vehicle are known, at each instant that the body is in motion the position-history of the IC can be determined relative to both a space-fixed reference system and a body-fixed reference system. The plotting-out of these successive ICs relative to the reference coordinate systems form what are known as the space (or fixed) centrode and body (or moving) centrode, respectively. Conceptually, the body centrode is virtually attached to the physical body and remains fixed

A more complex example is that of a wheel initially rolling on a flat surface without wheel slip that then undergoes braking with increasing wheel slip. As the wheel undergoes braking, a slip velocity (sliding) is developed at the wheel/surface contact point. For this slip-velocity condition, the IC is located at some distance below the surface plane. This is shown conceptually in Figure 3. Note that for this situation the velocity vectors at the center of the wheel and at the wheel/surface contact are both parallel to one another; the IC is then found to be the intersection of the line connecting the two origin points and the line connecting the tips of the velocity vectors. The body and space centrodes for increasing braking then take a form similar to that depicted in Figure 4. The body centrode shape is a spiraling curve originating at the wheel perimeter, and the space centrode a curve that moves progressively further below the surface plane. In this example,

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Performance of BMW Event Data Recorder (EDR) in Instrumented Barrier and Vehicle-to-Vehicle Crashes Robert D. Anderson Biomechanics Analysis Michael Rosenfield RSR Engineering

24 Collision Magazine - Volume 17 Issue 1

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bstract

BMW automobiles have Event Data Recorder (EDR) functionality to record crash-related data that is retrievable using the Bosch Crash Data Retrieve (CDR) Tool going back to the 2013 model year. However, unlike most automobile brands, there have been few, if any, prior crash test demonstrations of the performance and behavior of BMW automobile EDRs. This research was conducted as part of the Canadian Association of Technical Accident Investigators and Reconstructionists (CATAIR) 2022 Crash Conference. A description of CATAIR’s 2022 crash test demonstration program is outlined in “CATAIR 2022 Crash Conference,” which is also in this issue of Collision. A 2016 BMW X5 sport utility vehicle was subjected to a series of seven low speed front- and rear-to-barrier tests, followed by a high-speed vehicle-to-vehicle crash demonstration. EDR-reported pre-crash speed, longitudinal and lateral vehicle acceleration, and longitudinal and lateral delta-V was compared to reference instrumentation. The EDR reported driver and front passenger seat belt buckle status was compared to the test configuration, the ignition cycles increment was tracked, and the rear-to-barrier impact resulted in the deployment of the BMW’s active head restraints (AHR). Introduction Event Data Recorder (EDR) information from vehicles has become a common element in crash investigation and reconstruction analyses. As such, examples regarding the accuracy of EDR data are important to understanding how EDR data can fit into a situationally complete crash reconstruction analysis. Passenger vehicles manufactured for sale in the United States after September 1, 2012, are subject to the provisions of Code of Federal Regulations (CFR) Title 49, Section 5631 (49CFR563 which may also be referred to as “Part 563”) requiring manufacturers of passenger cars, light trucks and SUVs who elect to install a device or function in a vehicle which meets the regulation’s definition of an “Event Data Recorder” (EDR) to record a specified set of data parameters and make the data access and retrieval publicly available. As a consequence of the Part 563 requirement that after September 1, 2012, a publicly available tool be in place within 90 days after the first sale of a vehicle equipped with an EDR, a number of automobile manufacturers’ vehicles, including BMW, became Bosch CDR supported beginning in the 2013 model year. Literature Review Lawrence et al.2 compared three different 2002 GM vehicles' pre-crash speeds to 5th wheel data at various speeds. They concluded that the preevent speeds reported by Sensing Diagnostic Modules (SDMs) of some GM vehicles overestimated vehicle speed by up to 1.5 kph at low speeds and underestimated vehicle speed by up to 3.7 kph at high speeds. In a comparison of the SDM recorded pre-crash speed data during an acceleration maneuver case for a 2006 GMC Envoy Denali by Bare et al.3, the average error for each run was always less than 1.0 mph and the maximum error was 1.3 mph. During acceleration and braking runs, the maximum difference in the SDM recorded vehicle speed data was 1.5 mph and the average error was within 0.8 www.collisionpublishing.com

Collision Magazine - Volume 17 Issue 1 25

Personally Identifying Information -Katarina Juric

Collision Magazine - Volume 17 Issue 1

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ll data that might be used to identify a specific person is considered personally identifying information (PII). In order to successfully identify a person, PII may be used alone or in conjunction with other pertinent data. It may include direct identifiers, like passport information, which can uniquely identify a person, as well as quasi-identifiers, like race, which can be combined with other quasi-identifiers, like date of birth, to successfully identify an individual. As the legal system in the USA is built of diverse regulations and different federal and state laws, the definition of PII is not as consistent or a structured as the personal data established in the GDPR1 for the countries in the European Union. To begin with, it is challenging to distinguish between PII and personal data because PII is defined by numerous laws, rules, and policies, including: Act concerning Health Insurance Portability; American Labor Department Federal Trade Commission; Act Protecting Children’s Internet Information; American National Standards Institute. Different sources define PII or particular components of it. When it comes to really establishing a list of minimum things that should be anonymized and what constitutes private, personal data, this leads to a lot of minute variances. Due to the fact that the European rule includes the connection between the personal data and an identifiable individual, which is frequently not as obvious, the GDPR’s definition of personal can occasionally appear wider than the definition of Personally Identifiable Information in the US. Any data that may be used to directly or indirectly identify a person is considered personally identifiable information. The most practical way to determine what information is and isn’t Personal Identifying Information in practice is through individual assessment and paying attention to the procedure, law, regulation, or standard governing your particular State, industry, or field of application. Some examples of PII include the subject’s full name, phone number, passport number, residential address, social security number, driver’s license number, email address, and other digital information like IP address and geolocation. Some things, such as biometric data or medical information, are regarded as sensitive data. Yet, when contrasted to the GDPR’s definition of personal data, this can be somewhat ambiguous. Certain PII definitions in the US exclude IP addresses and cookie IDs, which directly contradicts the GDPR definition. The GDPR offers standards for businesses and organizations regarding how they should manage data pertaining to the people they engage with. It has made it simpler

for EU citizens to comprehend their rights with regard to how their personal information should be utilized. According to the GDPR, information is considered “personal data” if it can be used to directly or indirectly identify a specific person, including through the use of online identifiers like their name, an identity number, IP addresses, or geographical information. If online identifiers reveal details on a person’s physical, physiological, genetic, mental, economic, cultural, or social identity. In some cases, even details about a person’s occupation, hair color, or political views may qualify as personal data. The environment in which the data was gathered and whether a data subject might be directly or indirectly identified usually determine this. Most people think of phone numbers and addresses when they think of personal data, however there are many different identifiers that might be considered personal data. GDPR-related personal data does not include: information pertaining to a deceased person, proper anonymization of the data, information on businesses and government entities. Anonymization and Pseudonymization When data is made anonymous, it loses its personal nature because it is no longer possible to identify a specific person. But in order for data to actually be anonymous, anonymization must be permanent. Personal data still includes information that can be used to re-identify an individual even after it has been encrypted, de-identified, or pseudonymized. In order to provide the European Union with a unified set of privacy laws, the GDPR was introduced in 2016. Only retain this data for as long as it serves its intended purpose. This information should also be encrypted and/ or pseudonymized, especially if it is considered sensitive data. Pseudonymization is the process of masking data by swapping out any identifying or traceable information with made-up identifiers. Pseudonymization has several limitations, despite the fact that it can be a fantastic approach to safeguard the confidentiality and privacy of personal data. Although a person cannot be directly identified from pseudonymous data, they can directly identified from pseudonymous data, they can still be indirectly identified rather readily. Any information related to a person’s friends list or login details on social media. Radio frequency identification (RFID) codes—RFID chips typically include an easily recognizable, singular number that distinguishes any item to which it is attached and can be used to identifytify a

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Collision Magazine - Volume 17 Issue 1 45

THE EDR USER’S SUMMIT™ RETURNS “FEBRUARY 2024!” February 5-7, 2024. Moving to a different hotel but still near Houston’s Bush Intercontinental airport, the EDR User’s Summit will pick up where we left off before the lockdowns bringing back the only true wide ranging EDR data-centric Summit to be found anywhere. Do not miss EDR User’s Summit 2024!

Check out the Data Analysis Optional Add-On Session for Toyota Vehicle Control History (VCH – “Techstream”) At the Summit, Russ Casella, a Toyota in-service trainer, will cover Toyota VCH data in Techstream for all users in a general session. For a deeper dive, join the optional post-Summit workshop after the Summit on 2/7, 1:30–4 PM, where Russ explores detailed VCH data with hands-on applications. Bring your laptop for a unique Techstream training experience! 48

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To register and find more imformation about the summit, please go to: collisionpublishing.com and click on EDR Users summit. Those qualified to attend the Collision Safety Institute’s Technician Train-The-Trainer Course will have that opportunity February 4,2024. Shanon Burgess

Bill Rose

This timely and thorough presentation is an examination of the various types of data that can be extracted from smartphones, including location (GPS and speed) information, call logs, text messages, app usage, device activity, and sensor data followed by a look at recent testing to examine the connection between mobile device use and the EDR data date/time stamp such as that found in the GM FCM or ASCM systems.

Bill Rose from Bosch will present in this longstanding feature of the EDR User’s Summit™, this is an in-depth overview of what’s new and what may be coming soon to the Bosch Crash Data Retrieval tool. Will there be new system coverage? What is going on with the possible GUI revision? How will changes in the CDR Tool process impact how I use the tool in the field? Attendees can expect this and more!

Don Floyd

What’s New with GM EDRs 2024. Covering new GM system supported by the Bosch CDR tool, what Bosch interface to use with the new supported modules (CANPlus vs CDR 900), this presentation will cover: Pedestrian Protection System, SDM-50 Airbag Control Module, Active Safety Control Modules, and Forward Camera Module. Learn more about what parameters can be recorded, what are the event recording triggers, what are the event overwrite conditions, and the Active Safety Control Module and Front Camera Module data collection and image handling operations.

Charles Getz

Heavy Vehicle EDRs are continuously evolving. This presentation will cover the latest developments in the HVEDR world. Topics will include the newly released systems in Detroit Diesel, Paccar, Mack, and Volvo. Electric truck data will also be discussed.

Using GM Active Safety Module EDR Data with Case Examples. Learn more about the operation of GM Active Safety Systems supported by the Bosch CDR tool. Hear from a subject matter expert how to effectively manipulate vast quantity of Active Safety Control Module and Forward Camera Module EDR data and how to apply it in real-world case examples.

As a long-time Toyota inhouse trainer heavily involved in Techstream and Vehicle Control History, Russ will be sharing his wealth of information on the best ways to access and use VCH data.

Don Phillips

Working with Nissan crash data and something doesn’t “look right...” the delta-V polarity seems backwards, data elements are marked “clipped” but the sensors must be able to measure more than the data shows. This presentation will look at documented methods of identifying where Nissan data polarity is reported backwards and what “CLP” really means - and doesn’t mean.

Tommy Beetham

Russell Casella

Shawn Gyorke

Shawn is arguably the most well known go-to source for everything related to Hyundai and Kia EDR data and will share a bit about changes to the system and interesting data sets as seen in real-world applications.

Chris Medwell

A case study where Pre-Crash “Speed, Vehicle Indicated” was misreported by 50% and how the author was able to identify and create a test method for that anomaly and then where that error was corrected in the CDR Tool Software.

Ramon Homan

Presenting a unique look at Automated Traffic Signal Performance Measures and data sets captured by state traffic control authorities which might augment EDR data.

Wes Vandiver

Vehicle data useful to crash investigators can go beyond the traditional evidence found in airbag control modules. This presentation on Vehicle System Forensics will discuss the acquisition of data elements such as vehicle speeds, historical locations, connected devices, events, and system configurations that can be acquired from modern vehicles.

W. R. Rusty Haight

What do terms in Tesla CAN Bus data sets really mean? What is the range for the parameters? Will the CAN bus data elements be the same across all Tesla models? How does one get CAN bus data in the first place? These aspects and more of the increasingly common Tesla CAN data isn’t well understood or documented. This presentation looks to change that.

Tim Reust

Jason Chilson

Tim’s presentation will focus on Toyota Safety Sense (TSS) Testing and the results of over 65 instrumented tests conducted to trigger the Pre-Collision System resulting in PCS, Sudden Braking History and ABS Operation records. Tests were conducted at speeds between 25 to 70 mph.

Jason will explore case studies looking at GM’s Frontview Camera Module (FCM) data and photos in practical application real-world scenarios and then associate that analysis with testing examples. His practical approach will go hand-in-hand with the other active safety systems presentations and offer a different perspective on the data and its application.

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Trigger counts marked “Invalid” in Toyota EDR data - Part 1 - W. R. “Rusty” Haight

- Collision Safety Institute

oyota Event Data Recorder (EDR) data first became accessible using the Bosch Crash Data Retrieval (CDR) Tool with the release of CDR software version 4.0 in March 20111. Toyota data translation reports generated from the retrieved data have generally included a unique data element; one not found in the same way in data translation reports from other manufacturers’ systems: a “trigger count.”2 The “Trigger Count”2 as seen in Toyota data translation reports is normally identified by the acronym “TRG” as found in the element identifier “TRG Count” or in the normal numbering convention TRGn (i.e.: TRG2, TRG11, or TRG65). In some Toyota data translation reports, end users have found that the numbering convention appears to have failed and the TRG number is instead marked “Invalid” or, in some cases, “N/A.” Figures 1 and 2 are offered as examples of how that “TRG Count” may be observed to be marked “Invalid” or “N/A” under the column heading “TRG Count.” This apparent anomaly can be found in Toyota systems identified as part of the ECU/EDR Generations3 04EDR, 06EDR, 12EDR, 13EDR, 15EDR, and 17EDR. For this paper, the word “anomaly,” in various forms, is used to mean a translated data element or data description

that deviates from what might be considered otherwise expected in a data set were compared to the majority of like data sets. It doesn’t necessarily mean the anomalous data is “wrong”4…it is just different. We know that “digital Data, by virtue of its binary nature, is either right or wrong.”4 Here, the explanation of the source of the anomalous data and the identification of the conditions bringing it about in the various Toyota airbag control module (ACM) types suggests that that the data isn’t “wrong” as it relates to the identified conditions and meaning of the translated or reported values, it just isn’t reported as one might normally expect to find it and that may complicate an analysis when the analyst tried to apply that data. Based on a review and analysis of almost 27,000 Bosch CDR Tool data files (*.CDR and *.CDRx files) which were distilled to some 5,000 Toyota systems files5, this paper will explore under what circumstances a Trigger Count may be marked “invalid” in a CDR Tool data translation report, and present a more detailed explanation of the meaning of the “invalid” indicator than that found in current Toyota Data Limitations narratives or Bosch CDR Tool Help file. In Part 2 – in the next issue of Collision Magazine – options for confirming or verifying the represented order of events in a Toyota data transla-

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What Is Tesla I Sentry Mode And How Does It Work? ntroduction

All data that might be used to identify a specific person is considered personally identifying information (PII). In order to successfully identify a person, PII may be used alone or in conjunction with other pertinent data. It may include direct identifiers, like passport information, which can uniquely identify a person, as well as quasi-identifiers, like race, which can be combined with other quasi-identifiers, like date of birth, to successfully identify an individual. As the legal system in the USA is built of diverse regulations and different federal and state laws, the definition of PII is not as consistent or a structured as the personal data established in the GDPR (1) for the countries in the European Union. To begin with, it is challenging to distinguish between PII and personal data because PII is defined by numerous laws, rules, and policies, including: Act concerning Health Insurance Portability; American Labor Department Federal Trade Commission; Act Protecting Children's Internet Information; American National Standards Institute.

- Rehan Arif

Different sources define PII or particular components of it. When it comes to really establishing a list of minimum things that should be anonymized and what constitutes private, personal data, this leads to a lot of minute variances. Due to the fact that the European rule includes the connection between the personal data and an identifiable individual, which is frequently not as obvious, the GDPR's definition of personal can occasionally appear wider than the definition of Personally Identifiable Information in the US. Any data that may be used to directly or indirectly identify a person is considered personally identifiable information. The most practical way to determine what information is and isn't Personal Identifying Information in practice is through individual assessment and paying attention to the procedure, law, regulation, or standard governing your particular State, industry, or field of application. Some examples of PII include the subject's full name, phone number, passport number, residential address, social security number, driver's license number, email address, and other digital information like IP address and geolocation. Some things, such as biometric data or medical information, are regarded as sensitive data. Yet, when contrasted to the GDPR's definition of personal data, this can be somewhat

riving safely and protecting yourself, your family, and your vehicle is more important than ever these days. If you're a Tesla owner looking for an extra layer of security, then you have to be familiar with Tesla Sentry Mode. It is configured with Autopilot Hardware HW 2.0 or newer. Video recording facility is available on HW 2.5 models built after August of 2017. Tesla has two separate programs, Tesla Dashcam, and Tesla Sentry Mode. We will explore Tesla Sentry Mode here. Tesla Sentry Mode is designed to act as an additional deterrent against theft or vandalism by monitoring your vehicle's interior and exterior from multiple cameras installed in its frame, Including front, rear, and side cameras. It uses the camera images from the front main cam, side repeater cams, backup cam, and an inertial measurement unit (IMU). Using the cameras and the IMU sensor, this mode can alert owners via mobile app push notifications so they can take immediate action if necessary. Read on to find out all there is to know about Tesla's Sentry Mode! How Exactly Does Tesla Sentry Mode Work?

Here's how Sentry Mode works in more detail:

Tesla's Sentry Mode uses the car's cameras and sensors to detect any unusual activity around the vehicle when parked and unoccupied. When Sentry Mode is active, the system will record video footage if it detects any movement.

There are three states:

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The car's cameras and sensors monitor the surroundings: When the car is parked and Sentry Mode is enabled, the car's cameras and sensors continuously monitor the area around the vehicle. Detection of movement : If the cameras and sensors detect any movement, such as someone approaching the vehicle, trying to open a door, or tapping on the car, Sentry Mode will be triggered. Once activated, the owner is alerted when they return to their car - allowing them to stay aware of any potential security threats. However, when triggered in an alarm state, the car's alarms will sound which may notify nearby persons and will send a push notification to the owner via their Tesla mobile app. Activation of recording: When Sentry Mode is activated, the car's cameras will begin recording video footage of the surroundings. The footage is saved to a USB drive connected to the car.

(1) No Response state: The vehicle appears to be off so that no alarms will sound and no recordings will be made. (2) Awareness State: The vehicle enters this state from a trigger, such as a pedestrian walking or the car sensing

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Moving Masses and Barrier Impact Dynamics Micky Marine SSi Phoenix, Inc.

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s automobile impacts go a vehicle running into a flat, fixed, and rigid barrier is about as straightforward as it gets. The vehicle approaches the barrier at some speed; makes contact with the barrier; deforms; bounces off at a diminished speed; and comes to a stop shortly thereafter. Within this seemingly simple impact scenario, however, are some fairly interesting nuances. Shaw et al.1 seem to be the first in the open literature to hypothesize on the notion of effective mass transfer during the impact due to vehicle crush, stating, in regard to lumped-mass modeling of barrier crash tests, that “…more accuracy could be realized if the crushed masses in the model were allowed to vary with vehicle deformation, thus simulating the actual effective transfer of mass during a crash.” Twenty years later, Fossat 2 delved further into this notion and noted that “During a frontal crash, the real pushing mass is a function of time, because important parts of the car are stopped against the barrier far earlier than the passenger compartment. This variation in mass does not allow to derive straightforward [sic] the force generated by the car body during the impact.” In treating the barrier impact as a variable-mass problem, Fossat presented an equation to determine mass versus time histories, and used these to determine the “force Fe(t) generated by the car structure during the impact” by multiplication of the mass versus time data with the accelerations measured on the car body. The variable-mass conceptualization has been reiterated by some researchers 3, 4, 5 and it has been opined that multiplying the data recorded via accelerometers attached to the undamaged portion of the vehicle by the total vehicle mass will result in an over-estimation of the impact force and energy. Others have noted that an integration of accelerometer-based force data out to maximum displacement results in an energy loss value very close to the known approach energy of the test vehicle, while also noting inaccuracies in the integration of barrier load cell data when compared to the approach energy [6] and [7]. Here we will explore this issue a little further, starting with an examination of the variable mass concept.

The change in momentum of the system of Figure 1 is expressed as:

The force on the system is then expressed as:

Taking the limit, and noting that the ∆m∆v term is a second-order term and vanishes when the limit is taken,the force is expressed in differential form as:

Where all parameters (F, m, u, v) can vary with time. Noting that this derivation is for the case in which masss leaving the system, it is equivalent to switch the sign on the (u – v) term and consider mass exiting thesystem to be negative transfer, and mass entering the system to be positive transfer. In doing so, we get:

Eguation 1

Variable-Mass Conceptualization Consider the situation where mass m, traveling at velocity v relative to a fixed reference frame, expels an incremental mass Dm traveling at a velocity u, also relative to a fixed reference frame, as depicted in Figure 1. From Newton’s Second Law, we know the force on a system is equal to the rate of change of the momentum (P) of the system and can be expressed as:

Figure 1: Variable Mass Momentum. www.collisionpublishing.com

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construction Tool,” Society of Automotive Engineers Paper No. 2000-01-0604, 2000

10. Greenwood, D., “Principles of Dynamics, 2nd Edition,” Prentice-Hall, Inc., New Jersey, 1988

5. Wood, D., Veyrat, N., Simms, C., and Glynn, C., “Limits for Survivability in Frontal Collisions: Theory and Real-Life Data Combined,” Accident Analysis & Prevention, Vol. 39, pp 679-687, 2007

11. Chao, Y., “Inertia Effect in Dynamic Impact Tests,” Society of Automotive Engineers Paper No. 2004 010814, 2004

6. Varat, M., and Husher, S., “Vehicle Impact Response Analysis Through the Use of Accelerometer Data,” Society of Automotive Engineers Paper No. 2000-01-0850, 2000 7. Bare, C., Peterson, D., Marine, M., and Welsh, K., “Energy Dissipation in High Speed Frontal Collisions,” Society of Automotive Engineers Paper No. 2013-010770, 20138. de Sousa, C., and Rodrigues, V., “Mass Redistribution in Variable Mass Systems,” European Journal of Physics, Vol. 25, 2004 8. de Sousa, C., and Rodrigues, V., “Mass Redistribution in Variable Mass Systems,” European Journal of Physics, Vol.25, 2004

12. National Highway Transportation Safety Administration Vehicle Crash Test Database, URL: www.nhtsa.gov/ research-data/research-testing-databases#/vehicle 13. National Highway Transportation Safety Administration Signal Analysis Software for Windows, URL: www. nhtsa.gov/databases-and-software/signal-analysis-software-windows 14. Hunter, R., Fix, R., Lee, F., and King, D., “Using Force-Displacement Data to Predict the EBS of Car into Barrier Impacts,” Society of Automotive Engineers Paper No. 2016-01-1483, 2016

9. Tiersten, M., “Force, Momentum Change, and Motion,” American Journal of Physics, Vol. 37, 1969

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Appendix A – Kinetic Energy Change Comparison

Figure A: 12015 Mitsubishi Mirage (#9030)

Figure A2: 2002 Daewoo Nubira (#4239) www.collisionpublishing.com

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Figure A7 : 2004 Toyota Highlander (#4930)

Figure A8: 2006 Ford Fusion (#5546) 100 Collision Magazine - Volume 17 Issue 1

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Go to www.collisoinsafety.net for class locations and schedules

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CATAIR 2022 Crash Conference Michael Rosenfield RSR Engineering

Robert D. Anderson Biomechanics Analysis

he Canadian Association of Technical Accident Investigators and Reconstructionists (CATAIR) was founded in 1984, initially to provide all accident investigators, the majority of whom were serving as Police Officers within Canada, a professional and affordable mechanism in which to meet and share experiences and ideas. The association has grown from the concept stage, with an original membership of fewer than 20, to a maintained membership of approximately 300. Membership is maintained throughout Canada, the USA, Singapore, Australia, and Brazil. The 2022 Crash Conference was held at the Ontario Police College, Aylmer Ontario, Canada.

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The college is on the site of WWII airfield, with a number of taxiways usable for testing. The largest is 75’ wide and 1600’ long, which allowed for a number of high-speed collisions. The 2022 CATAIR Crash Conference featured pre-conference front– and rear-to-barrier crash tests using a BMW X-5 SUV. The X-5 was equipped with active head-restraints. Reference instrumentation measured pre-crash and crash data to allow comparison with the EDR data from the Bosch-supported Airbag Control Module. ACM-measured delta-V was 6.8 mph rearward, and 7.5 mph forward. There were five front-to-barrier impacts with gradually increasing magnitude before a non-deployment event was recorded for an ACM-recorded impact speed of 10 mph. A rear-to-barrier impact created a deployment event with activation of the active head restraint in an ACM-recorded impact speed of 9 mph. The results of this testing is covered in more detail in “Performance of BMW Event Data Recorder in Instrumented Barrier and Vehicle-to-Vehicle Crashes”, in this issue of Collision Magazine. The second pre-conference test measured vehicle accelerations and occupant forces when running over the Stop Stick® tire-deflation device that has three Teflon coated hollow steel quills. This device causes the tires that run over it to deflate in 20 to 30 seconds. Attendees have the opportunity for an “on-scene” investigation experience, plus full access to documented crash examples at known speeds, Delta V’s, etc. This wealth of information is useful in supporting or demonstrating collision principles, vehicle and occupant dynamics, vehicle performance, as well as the opportunity to compare reconstruction methods against actual test results. Certainly, the chance to compare the output from reference instrumentation to roadway evidence, EDR data, video analysis, etc. is invaluable. Specific examples of study from this test series would include type of events recorded by vehicles’ modules, as well as the accuracy and polarity of EDR reported parameters. Besides vehicle accelerations and Delta V’s, and occupant accelerations and seat belt load cells, the instrumentation included vehicle angular rates, and impact speeds measured using Racelogic VBOX equipment. The documentation package, which is included in the conference materials, includes photographs, on-board, ground based and aerial drone video, as well as on-board and off-board high speed video. www.

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From Crash 8, the Mini essentially cleared the barrier.

Summary Attendees had the opportunity for an “on-scene” investigation experience, plus full access to documented crash examples at known speeds, delta V’s, etc. This wealth of information is useful in supporting and demonstrating collision principles, vehicle and occupant dynamics, vehicle performance, as well as the opportunity to compare reconstruction and biomechanical methods against actual test results. Certainly, the chance to compare the output from reference instrumentation to roadway evidence, CDR data, video analysis, etc. is invaluable.

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Specific examples of study from this test series would include type of events recorded by vehicles’ Airbag Control Modules, accuracy of CDR reported parameters, postcrash decelerations, and the characteristic tire marks from the natural steering-induced rollover during Test 5, and the post-crash spin outs during Test 7.

Acknowledgements Thanks are due for the support and generosity of CATAIR, Ontario Police College. and the crash team, which includes: Crash Data Specialists, Accident Analysis and Reconstruction, 3 Axis Engineering, RSR Engineering, Biomechanics Analysis, and Collision Forensics, and many others.

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