Volume 16, Issue 1

ollision C

Volume 16 Issue 1

The International Compendium for Crash Research

Investigation of EDR Data

From a High Speed Crash with 3D Simulation

Crashology: EDR Delta-V The effect of tire friction

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Contents

Volume 16 Issue 1

inside 4

Letter From the Editor

5

Collision Magazine Info and Advertiser Index

6

features 6

28

60 72

90 96

Investigation of EDR Data from A High Speed Crash with 3D Simulation

by Brian G. McHenry

Analysis of the Event Data Recorder Information Obtained in Crash Testing of Supported and Pre-Supported Hyundai Vehicles

28

by Robert Anderson and Wesley Vandiver

Restitution, Impulse Space, and Orientations

by Micky Marine

Analytical Method for Correcting the Delta-V Reported by Toyota/Lexus/Scion Airbag Control Modules

by Robert Anderson, Michelle Hoffman and W. R. Rusty Haight

60

Development of a Test Procedure for Setting Non-Deployment (ND) Events

by Chris Medwell

Crashology: Event Data Recorder Delta V: The Effect of Tire Friction

by Wesley Vandiver and Robert Anderson

100 The 2021 and 2022 SATAI Crash Program

by Robert Anderson

90

case study 46

Case Study: Verifying EDR Data from a Ram ProMaster 1500 Van Collision

by Chris Medwell

106 Case Study Solution: Discovering and Explaining a CDR Data Anomaly

by Chris Medwell

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Letter from the editor Now that we seem to be "over the hump" with respect to COVID, we've started planning for the return of the EDR Summit in 2023. The last EDR Summit in 2020 was right before the widespread lockdowns and, since then, there have been a number of changes in the CDR Tool, coverage and module types available. The 2023 EDR Summit, tentatively planned at the end of Q1 2023, possibly Q2, would be a great place to catch up with the latest on EDR technology as well as reconnect with colleagues.

Some may have noticed that this issue of Collision - Volume 16, Issue 1 marks the first time that subscribers were offered a choice for the delivery format of Collison: a printed hard copy, a digital copy, or both. With any significant change like this there will be a learning curve on our end and an adoption curve on the end user's side. We are excited to offer Collision in the various formats as we move forward; however, we are sure there will be more changes or adaptations made to make the version each subscriber wants available.

Speaking of availability, the supply chain issues we at Crash Data Group have been experiencing have been easing a little and the backordered EDR products (Bosch, Tesla and GIT America) seems to be easing up. The inventory of CDR Tool components from cables to adapters seems to be getting close to pre-COVID levels.

Recently a huge shipment of backordered cables went out to end users and we expect to see more of that in the coming weeks.

In related news, the Crash Data Group is now an official distributor of the Hyundai and Kia EDR Tool. The agreement with GIT allows CDG to configure various kitting options to best suite your budget and needs. CDG can also renew Hyundai and Kia EDR software subscriptions. We have literally been working on this arrangement for years and are very pleased to offer the GIT EDR Tools in various configurations.

In this issue of Collision, there is the first of what looks to be several follow up articles associated with the Case Problem from Volume 15, Issue 2. The Brian McHenry article regarding the simulation of the very unusual crash highlighted as the case problem in the last issue is a lead-off article in this issue and delves deeper into the dynamics of that case. Similarly, a new case problem by Chris Medwell highlights the importance of paying close attention to the "What's new" in this version of the CDR Tool software list of changes.

Another reemergence in this issue of Collision and one we hope to be able to continue going forward is the discussion of crash tests conducted by organizations which (a) might highlight the organization for those unfamiliar with it and (b) give wider distribution to the availability of such data. In this issue, Bob Anderson discusses two years of SATAI crash test data.

I know the past two years have been a very trying time for everyone and I hope the worst is behind us. I look for-ward to seeing everyone in person at the 2023 EDR Summit and also continuing to provide fresh crash research content to all the loyal subscribers of Collision Magazine.

Scott Baker Managing Editor 4 Collision Magazine - Volume 16 Issue 1

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ADVERTISER INDEX

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COLLISION STAFF Scott Baker Sean Haight Tonya Baker

4N6XPRT Systems Bosch CDR Tool (CDG) Collision Magazine Collision Safety Institute (CSI) Crash Hub Engineering Dynamics Forensic Mapping GIT EDR Tools (CDG) Leica Geosystems Lightpoint Tesla Virtual Crash

PAGE Inside Back Cover 59 71 99 88-89 Inside Front Cover 45 Back Cover 2 1 112 44

Owner, Managing Editor Senior Editor Advertising Manager

SUBMIT AN ARTICLE If you would like to submit an article to be published in Collision please use the following link:

www.collisionmagazine.com/submit BACK ISSUES All back issues of Collision Magazine are now available in digital format - please visit:

https://crashdatagroup.com/collections/ collision-magazine-back-issues All rights reserved, © 2022 Crash Data Group Inc. The opinions and conclusions expressed in this publication and any associated data 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.

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Fo ll ow -u p

CA SE

PR OB LE M

Investigation of EDR Data from A High Speed Crash with 3D Simulation

Volume 15, Issue 2 of Collision Magazine contains a case problem article entitled "Did you find any errors when you read through the data?" by W. R. Rusty Haight & David W. Sersen

Brian G. McHenry McHenry Software Inc

ntroduction Volume 15, Issue 2 of Collision Magazine contains a case problem article entitled "Did you find any errors when you read through the data?" by W. R. Rusty Haight & David W. Sersen.

I

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The case problem documents a real-world crash, captured in part on video, where both involved vehicles have similar, nearly identical data sets. Both vehicles had EDRs (Electronic Data Recorders). Both vehicles were General Motors (GM) vehicles, both are "49CFR563 compliant" [1]

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in terms of the data sets recorded. They are from the same direct to module (D2M) cable family (the "F00K108454" D2M cable family of GM ACMs). The data translation reports for both are almost identical including much of the Data Limitations text. The most significant difference is the actual module variant. One vehicle – a 2013 Buick LaCrosse (Allure) – had what is identified as an "SDM10Pconti" airbag control module (ACM). The other involved vehicle, a 2017 Chevy Tahoe, had an ACM identified as a "SDM30-delphi."

The first reason for a review of the case problem is the fact that the crash had some EDR (Electronic Data Recorder) anomalies, documented in the article, which demonstrate and caution that EDRs are not infallible, and you always must use caution when reviewing the EDR results. EDR data and information provide additional data for crash reconstruction which needs to be carefully analyzed in concert with other analyses and examinations to come to final conclusions on each individual crash reconstruction.

The article brought up many important issues which need to be considered and addressed when reconstructing a crash with one, or two, EDRs. EDRs tell part of the reconstruction story…they are a great additional piece of the crash reconstruction puzzle however they can and do have issues/failures and don't tell you everything you need to know about a crash. The referenced article [2] included possibilities for corruption or inadequacy of the EDR data due to proximity of the EDR to the crush zone (does it possibly move during the crash? ), collisions wherein the accelerations on vehicles may exceed the limitations of the maximum acceleration which can be recorded by the EDR (many have 50 g-unit limits which represent an approximation of the actual limit) and there are other items which also need to be considered.

A second reason for interest in the subject crash is that although one vehicle was at an extremely high speed (>100 MPH closing speed), the combined speed is like what might be encountered in 2 lane at-speed highway crashes so the anomalies brought up in the article are applicable to many highway crashes.

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Summary of the Crash The crash occurred in May 2019 when a speeding 2013 Buick LaCrosse, which weighed approximately 3693 lbs.

(1675 kg), crashed into a stationary 2017 Chevy Tahoe sheriff vehicle which weighed approximately 5550 lbs.

(2517 kg). During the inline head-on impact both vehicles sustained significant frontal damage [Figure 1]. [2] As a result of the collision the Tahoe was pushed backwards approximately 172 feet and rotated approximately 180 degrees. The Buick continued after the collision to travel forward approximately 228 feet down the road to its position of rest [Figure 2] The Tahoe's Pre-Crash EDR Data table indicates that during the last 5 seconds leading up to the crash, the deputy slowed from 7 mph (12 km/h) to a stop; his speed is very clearly 0 mph from about the -3.0 sec Pre-Crash Data sample to the -0.5 sec sample: that being the last pre-crash sample before "algorithm enable", which generally indicates the point of collision. [Figure 3].

The Buick Pre-crash EDR data indicates that the vehicle was accelerating from 106 MPH at 5 seconds prior to the impact to 109 MPH at the last recorded value approximately 0.50 before the "algorithm enable." [Figure 4].

In the case problem article, the reported Delta-Vs of the Buick and Tahoe do not agree with the physical laws when we calculate: •

What the Delta-V of the Tahoe should have been in this crash for the EDR reported Buick Delta-V

•

What the Delta-V of the Buick should have been in this crash for the EDR reported Tahoe Delta-V.

From the referenced article [2] “The first might be found in the data table "System Status at Event (Event Record 1)" where we see the data element "Maximum Delta-V, Longitudinal (Maximum Longitudinal SDM Recorded Vehicle Velocity Change for FSR Event) [3] MPH [km/h]" and the translated value is "-48 [-77]. [4] That element is coupled with the item, from the

Figure 1: Photographs of the damage to the vehicles in the subject crash 8 Collision Magazine - Volume 16 Issue 1

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Figure 2: Overhead view of the collision site

Figure 3: Tahoe Pre-Impact EDR information

Figure 4: Buick Pre-impact EDR information same data table: "Time, Maximum Delta-V (Time From FSR Time Zero to Maximum Longitudinal SDM Recorded Vehicle Velocity Change)(msec)" and the translated value there of "138 (ms)." What this says is that the airbag control module (ACM) captured acceleration and then cal-

culated the Delta-V out beyond 138 ms, however, at 138 ms, the ACM found the Maximum Delta-V which was recorded as -77 km/h (-48 mph) rounded to the near¬est 1 km/h for the resolution called out in 49CFR563. [5]

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The reported Delta-V for the Buick from the EDR data was between 45.3 and 46.6 MPH The "Maximum Delta-V, Longitudinal" for the Tahoe is reported as -48 mph (-77 km/h) – coincidentally the same as that recorded for the Buick – but, given the difference in their weights, one of those values can't be right.

From the article [2] “…the reported Delta-V for Tahoe (48 mph (77 km/h)), the average weights of the involved vehicles as previously discussed, and an estimate for restitution of 0.1 we find that the closing speed of the Buick "should be" about 109110 mph (175-177 km/h) as seen in Equation 5. Again, as an interesting aside, if one were to discount restitution – because "it doesn't really make a difference in 'big Delta-V' crashes" – the Buick closing speed, given the information at hand, would be calculated to be 120-121 mph (193-195 km/h).

This seems like it might have already been answered, but to be clear at this point in this Case Problem solution, given the data available, the Delta-V for the Buick should be about 72-73 mph (116-117 km/h).

The article poses the question •

“What might the reason be for the discrepancy with the Buick Delta-V data?”

The detailed approach to investigation was to reconstruct the crash with a 3D crash simulation program which will provide detailed dynamic responses from which the question can be investigated.

Research approach to evaluate the subject crash and EDR data Some researchers in the field of highway safety tend to view experiments, whether part or full scale, as being more real and believable than analyses. At least part of this tendency stems from the fact that physical experiments can be seen and photographed. Many physical experiments are poorly defined and controlled. Instrumentation errors sometimes yield individual items of response that are not compatible with each other.

Computer analysis can help by allowing the direct observation of computer “experiments". For example, in the series of physical experiments that were performed to validate the 3D simulation program HVOSM (Highway Vehicle Object Simulation Model) [6], several instrumentation difficulties were revealed by the comparisons with analytically predicted results.

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It is not intended to suggest that computer simulation can ever eliminate the need for physical experiments; rather, the intention is merely to point out the fact that computer simulations can serve as valuable aids for interpreting the results of physical experiments with nonlinear systems, as well as for interpolation and extrapolation to other combinations of test conditions.

For the subject questions on EDR issues we will merge the known facts and data from the crash with computer simulation to help identify and explain the source of the EDR anomalies. The subject crash included damage and trajectory information, and EDR data for both vehicles. So it is a good example of a somewhat ‘full scale test’ type crash in which we can use a simulation program to help evaluate the crash and answer questions related to anomalies found in the EDR data.

The 3D simulation program we used to aid in the evaluation of the crash and the EDR data is the msmac3D (McHenry SMAC 3-Dimensions) program. Msmac3D is a combination of two programs, HVOSM (Highway Vehicle Object Simulation Model) and SMAC (Simulation Model of Automobile Collisions), originally created and developed by Raymond R. McHenry, while at Calspan and which Ray and I merged together as a part of a research project in 1998 [Reference 7] The HVOSM is a 3D vehicle simulation model in which the vehicle has fifteen degrees of freedom: 6 for the sprungmass, and up to 9 for the unsprung-masses. Tire side forces are generated according to equations allowing for saturation to occur at large slip angles. The “friction circle” and the "friction ellipse" concepts are used to simulate the effects of braking and traction on the side forces. The simulated suspension forces include progressively stiffening, energy dissipating limit stops and a combination of coulomb and viscous damping. The sprung mass is represented as a rigid body with a peripheral layer of homogeneous, isotropic, deformable material. The assumed properties of the peripheral layer, with dynamic pressure directly proportional to depth of penetration, were based on the results of dynamic and static crush tests of automobile structures [7].

The SMAC computer program is a 2D time-forward simulation model which includes a complex collision algorithm for monitoring, detecting, and modeling the collision interactions of motor vehicles. With SMAC you set up a mathematical "full scale crash test" using the vehicle weights, dimensions, and other properties, you set the initial positions, headings and velocities and start the simulation run. The simulated vehicles collide and run out to rest. You then compare the SMAC predicted positions, ori-

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entations at rest and predicted damage with the accident evidence [8].

In 1998, I was hired by CBS News to reconstruct the Princess Diana crash for the television program “48 Hours”.

We were provided the survey information for the tunnel, the approximate path and tire marks left by the vehicle, the vehicle damage and other vehicle information (crash tests for structural characterization) and we used the program, mSMAC3D (the McHenry Simulation Model of Automobile Crashes 3 Dimensional), to simulate the vehicle traveling into the Pont de l'Alma road tunnel in Paris, France, and striking the bridge support post. In the Pont de l’Alma tunnel they do not have guardrails or barriers in front of the bridge support posts. The results were presented in June 1998 and August 1998 . The eighteen-month French judicial investigation which concluded in 1999 correlated closely with the speeds and findings of our investigation and crash reconstruction and simulation. Until the early 2000s, the limitations in processing speed of personal computers limited our continued development of the mSMAC3D model to simple internal research. Since early 2000s, and with the expanded computer capabilities, the msmac3D has been a commercially available 3D crash simulation reconstruction tool.

Topics of Investigation of the Buick EDR There are four possible reasons for the Buick EDR anomaly to be investigated: 1. Was the EDR anomaly due to the amount of vehicle pitch during the collision?

a. Closely reviewing the underlying acceleration data found in the data translation report clearly shows three distinct "flat spots" in the Buick crash pulse acceleration data at approximately 44 g's each. It is entirely possible that these represent a point where the accelerometer has reached the actual limits of its range ("approximately" 50g's) not to mention the potential for over-ranging and the possibility of physical damage to the accelerometer in the crash.

3. Was the EDR anomaly due to some issue or limitation in the EDR Delta-V calculation logic? a. Other possible explanations include EDR Delta-V integration data start and end times and sampling increment size and/or whether the offset of the EDR to the CG affected the results of the integration of the acceleration to produce the incorrect impact speed change aka Delta-V? 4. Was the EDR anomaly due to the EDR proximity to the crash zone and movement during the crash? a. Figure 7 provides a schematic of the OEM location of the EDR as compared to the damage photo which shows significant change to the area of the EDR location. From the article it was suggested that the reason for the console damage and EDR movement was due to the extensive crush in the collision wherein the engine was pushed under the vehicle passenger compartment. The movement of the engine lifted and shifted the console in the passenger compartment.

2. Was the EDR anomaly due to limitations of the EDR data collection and the approximate 50 g limit?

3. Was the EDR anomaly due to some issue or limitation in the EDR Delta-V calculation logic?

4. Was the EDR anomaly due to the EDR proximity to the crash zone and movement during the crash?

1. Was the EDR anomaly due to the amount of vehicle pitch during the collision? a. Figure 5 displays some frames from the convenience store security camera video which show a significant amount of pitch during the crash.

2. Was the EDR anomaly due to limitations of the EDR data collection and the approximate 50 g limit?

Figure 5: Frames from the video of the subject crash showing pitching of both vehicles

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Figure 6: EDR Acceleration and Delta-V traces for the subject vehicles, Tahoe (left) amd Buick (right) Simulation Analysis of the Subject Crash and EDR data To begin the subject analysis, a preliminary msmac3D simulation was performed of the subject crash as a baseline from which to allow testing various possibilities which might have produced the EDR anomalies. The subject scene photo was scaled and loaded into the simulation [Figure 8], the approximate elevation changes of the roadway were then automatically loaded from Google Map

information and the vehicles were loaded with default specifications based on make, model and year. Next the vehicle specifications were edited to include the known approximate weights of the vehicles at the time of the crash combined with other known data.

Post impact approximations of wheel drag were entered since the front wheels of both vehicles were crushed/ pinned and/or separated in the subject case.

Figure 7: Location of and damage to area of the location of the EDR in the vehicle console 12 Collision Magazine - Volume 16 Issue 1

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The msmac3D program is an iterative procedure where you simulate a “full scale crash test” at assumed or mathematically estimated speeds. The starting speeds can be obtained through simplified linear momentum approximation methods, EDR reported contact speeds or simple hunches. In the subject crash we had the EDR reported speeds from 0.5 seconds before ‘contact’, aka the ‘algorithm enable’ time (0 MPH for the Tahoe, 109 MPH for the Buick).

wheel separated from the vehicle. With some adjustments we obtained a good first approximation of the crash with the msmac3D simulation.

The results of the preliminary msmac3D simulation of the crash are shown in Figure 9 through Figure 16.

•

The msmac3D simulation was run and the results were evaluated to determine if the simulated damage location and extents approximately matched the damage indicated in the photos. [Figure 1] and does the trajectory distance and rotation approximately match the scene evidence [Figure 8].

Measurements and/or scans should supplement vehicle and scene photographs and estimates for the best characterization of the scene and vehicle evidence in order to perform the most accurate crash reconstruction and simulation. However, this preliminary crash reconstruction was simply created to provide a baseline crash reconstruction dataset for testing theories on what might have caused the anomalies in EDR data.

Msmac3D was then iterated by adjusting impact positions and speeds (as required) until a good preliminary approximate match of both the damage and trajectory data from the simulation matched the scene and vehicle damage information. After a few iterations of the collision offset (since the speeds of impact were known), some adjustments were made to the post-impact drag due to the extensive damage to the front wheels. On the Buick the front wheels were pushed rearward and on the Tahoe one

The time of impact was 1.546 seconds in the preliminary msmac3D crash reconstruction.

•

We could have started the simulation at contact so then 0.0 seconds would be the collision point however we wanted to include simulation of the pre-impact high-speed travel of the Buick through the intersection and to the point of impact to include any possible elevation changes on the Buick suspension and orientation at the point of collision.

•

To compare the EDR data with the msmac3D simulation output we simply added a time to adjust the EDR data. For best results we added 1.555 seconds to the Tahoe data and 1.545 seconds to the Buick data. These values were used for all charts displayed in this report.

•

The impact speeds were 0 MPH for the Tahoe, 109.1 MPH for the Buick

•

The Impact Speed Changes (Delta-V) were

•

•

45 MPH for the Tahoe and

•

69.3 MPH for the Buick.

The Tahoe (Veh1) msmac3D preliminary crash reconstruction comparison with the EDR results show

Figure 8: Overhead view of the collision site with POI, POR and other information labeled www.collisionpublishing.com

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a good correlation for the acceleration waveform and Delta-V time histories [Figure 12] •

The Buick (Veh2) msmac3D preliminary crash reconstruction comparison with the EDR results do not have an acceptable correlation [Figure 13].

The first check of the msmac3D preliminary crash reconstruction simulation results was to test Newton’s 3RD law to confirm that Mass1*Delta-V1 = Mass2*Delta-V2.

The results correlate well for the collision partners.

Note that a simple application of the momentum-based calculation of results may include some variation by a small amount. This is particularly evident In many lower speed collisions where there sometimes is a larger percentage difference.

In motor vehicle collisions we do not always get Mass1*Delta-V1 = Mass2*Delta-V2 because of external forces such as tire forces and other external forces (such as structures scraping the terrain during the collision interaction). When evaluating collisions with one or both vehicles having an EDR you may note this phenomenon depending on impact configuration and/or whether there was pre-impact braking which continued for part or all of the collision for one or both vehicles. As a simple example consider a side impact collision where one vehicle is pushed sideways. Energy is lost during the collision through the tires as external forces which resist the vehicle lateral motion. For more discussion on this topic see Reference [9].

The total Delta-V of the Buick from the msmac3D preliminary crash reconstruction simulation was 71.3 MPH (Figure 15). The Delta-V for the Tahoe was 45 MPH (see Figure 11).

Note that the total Delta-V value for the Buick in the msmac3D simulation includes the approximate 1.3 MPH

Delta-V which occurs after the collision interaction with the Tahoe due to additional external forces. The external forces are due to the rims and/or structure interacting with the roadway.

The logic contained in the EDRs of the subject vehicles for the calculations of Delta-V have not been investigated or determined for this article however they most likely are slightly different than for the msmac3D collision simulation post processing Delta-V calculations: In a msmac3D simulation: •

The program knows the accelerations of each vehicle at every millisecond during a collision interaction (the presence of collision forces) and/or when accelerations are being caused only by other factors (the presence of external forces).

•

The program calculates the resulting acceleration for each vehicle for each millisecond in time during the collision and uses that resultant acceleration value in the calculation of the Delta-V for each vehicle.

•

Calculating the Delta-V for each direction (longitudinal, lateral, and vertical) can have issues if the direction of any of the components reverse and change algebraic sign as it may reduce calculated Delta-V for the individual directional component.

•

The logic in the smac3D program starts the Delta-V calculations at the first instance the acceleration goes above 1 G-unit. The Delta-V calculation continues until the acceleration goes back below 1 G-unit. Additional logic was added to catch momentary sign changes in the acceleration and to combine them if the vehicles are still interactive (if there are still collision forces)

Figure 9 Overhead multiple exposure graphics of preliminary msmac3D reconstruction of subject crash and match with scene evidence 14 Collision Magazine - Volume 16 Issue 1

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•

The Principle Direction of Force (PDOF) for each vehicle is determined at the time of maximum acceleration for each vehicle during a collision.

The logic for EDR Delta-V calculations are not known at this time however there are some obvious issues: •

EDRs do not know what is causing the accelerations and what is happening to the collision partner (or if it is not a collision partner, it might be a tree or wall)

•

EDRs Delta-V logic must simply look at the acceleration time history as recorded.

•

Whether EDRs individually calculate the Delta-V from the resultant acceleration at each time increment (like msamc3D does) or whether EDRs calculate the Delta-V for each component separately (longitudinal, lateral and vertical (if included)) is not known.

Figure 10: msmac3D preliminary crash reconstruc• tion stills at 1.8 seconds and 1.95 seconds

The EDRs have a lot of scatter in their measurement of the accelerations (jumping across the axis going

Figure 11 Impact (top) Separation (Middle) and Delta-V (bottom) summary of preliminary msmac3D simulation www.collisionpublishing.com

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Figure 12: Tahoe EDR measurements compare with msmac3D Delta-V with msmac3D Preliminary Crash Reconstruction positive and negative by large amounts). Understanding what logic controls the start and end time for the EDR Delta-V calculations is important. The logic can make a difference in the resulting EDR Delta-V results.

As part of our RICSAC-97 research [10] we evaluated variations on the location of the accelerometers in the vehicle in full scale tests and the effects of those differences in the Delta-V results. We also investigated the start and end times for the Delta-V calculations. To assist in our analysis, we created a post processing routine called smacTHP (SMAC Time History Program). The program was a part of our research documented in the SAE Paper 97-0961 [10 ]. As part of that research, we found two different ways Delta-V is calculated:

•

TEST EQUIVALENT Delta-V Calculation: As part of that research, we found that test facilities may separately calculate the Delta-V for each directional component (longitudinal (X), Lateral (Y) and Vertical (Z) and then combine those Delta-V values to determine the total Delta-V.

•

SMAC EQUIVALENT Delta-V Calculations: The msmac3D program calculates the resultant acceleration for each time increment during a simulation and uses that resultant value in the calculation of the Delta-V.

•

Further discussion and presentation of Delta-V calculation procedures are contained in Reference 10.

Figure 13: Buick EDR measurements compare with msmac3D Preliminary Crash Reconstruction.

Notice the maximum X acceleration limit for the Buick 16 Collision Magazine - Volume 16 Issue 1

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Figure 14: msmac3D speed v time for crash reconstruction of subject crash The Delta-V values are slightly different between the msmac Collision summary (bottom part of Figure 11, where you see a separate 1.3 MPH Delta-V with no corresponding Delta-V for the Tahoe (Vehicle 1)) and the results from the smacTHP program in Figure 15.

In Figure 15 there is listed: •

Delta-V-RES which is the TEST EQUIVALENT Delta-V and represents the Sum of Squares of the individual Delta-V-X & Delta-V-Y

•

Delta-V-ACC which is the SMAC EQUIVALENT Delta-V and represents the Delta-V determined by Integration of Resultant Accel

For purposes of comparison with EDR data and determination of what might affect the results of the EDR outputs we will use the total Delta-V values as determined by the smacTHP program.

Figure 15 smacTHP calculation of the Delta-V for the Buick (veh2) is not responsible for the EDR anomaly. Also note that in the simulation there is only 17 degrees of pitch of the Buick which was less than the results from the report [2] where they used Tracker software [11] on the security camera footage and found that the Buick pitched up to approximately 27-30 degrees.

For this preliminary simulation investigation, we did not include the option to simulate the movement and deformation of the tires and suspension rearward with respect to initial location on the vehicle which would have allowed for more pitch angle. However, since the pitch response was after the collision interaction the additional pitch response would not have affected the EDR results.

For another demonstration of the effects of vehicle pitch effects on the EDR data we can compare a purely 2D (planar) analysis with the 3D analysis:

Simulation analysis of the Topics of Investigation of the Buick EDR In the following we investigate the topics related to the Buick EDR as listed earlier in this article: 1. Was the EDR anomaly due to the amount of vehicle pitch during the collision?

To address the first item of whether vehicle pitch can help explain the EDR results in Figure 16 we marked the area in red where the collision interaction between the vehicles occurs. The collision interaction is over before any significant vehicle pitch or roll response begins.

Note that the collision interaction is over 0.5 second before the peak pitch angle of the Buick so the pitch response

Figure 16: msmac3D Roll & Pitch Responses of Vehicles

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With msmac3D a crash reconstruction can be run in 3D or 2D (planar) mode. In real world collisions and 3D collision simulation models like msmac3D during collision interactions the vehicles can 3D translate (X, Y & Z) and 3D rotate (yaw (X-Y), pitch (X-Z) and roll (X-Y)) during the collision away from the collision interaction positions.

This allows an additional dimension (the Z or vertical direction) for the vehicle to travel during a collision interaction.

We refer to this as the “path of least resistance” behavior during collisions: Colliding vehicles rotate around and away from the collision area (the area of the vehicle structures) to try to minimize the forces and moments during the collision.

This can be modeled in a 3D computer simulation model like msmac3D because at every millisecond during the generally 50 to 150 milliseconds of crash interaction the actions of the forces and moments are modeled in 3 Dimensions.

In 2D analyses and simulations, for example when using a 2D simulation program in which all forces and moments are modeled for every millisecond during the collision interaction (like original SMAC or msmac3D when run in optional 2D mode), colliding vehicles can only translate (in X & Y, planar) and rotate in Yaw (X-Y planar). Therefore, the detailed forces and moments in identical 2D v 3D simulations can be quite different.

In this simple test we reran the preliminary 3D crash reconstruction simulation, using the msmac3D 2D option, to demonstrate differences which can occur between 2D and 3D analyses. This comparison is to shed further light on possible pitch and roll effects on the EDR measurements.

The results of the preliminary crash reconstruction rerun in 2D (planar) is presented in Figure 17 through Figure 20 In Figure 17 we compare the EDR data with a 3D and then 2D simulation of identical impact configurations.

Note that the 2D option limits the vehicle responses to the 2D X-Y plane: •

•

The Tahoe Delta-V •

Delta-V increased from 45 MPH to 50 MPH

•

Maximum Acceleration increased from 43 Gs to 56 Gs

•

Crash duration increased from 0.114 sec to 0.125 sec

The Buick •

Delta-V increased from 71 MPH to 76 MPH.

•

Maximum acceleration increased from 67 Gs to 85 Gs

•

Crash duration increased from 0.114 sec to 0.125 sec

A direct comparison of the 2D v 3D results create a dramatic demonstration of the phenomena we refer to as ‘path of least resistance’ where without the ability of the vehicle to lift, pitch and roll away and around the area of contact between the two vehicles in 2D, the X-Y planar structure must absorb more energy.

An additional item to note is that for 2D there is a range of speeds.

The reason for the range of speed in the 2D simulation is that the vehicle sees more lateral (Y) movement and acceleration than in the 3D (which has X-Y-Z). This also demonstrates how important it is to determine how the EDR logic handles fluctuations in the accelerations. Does the EDR logic ignore the fluctuations of the accelerations? If not, what signal or flag is used to trigger the start and end of the Delta-V calculations? This will be explored more in the next section.

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Figure 18: msmac3D crash reconstruction rerun in 2D mode (so planar X-Y 2D simulation analysis) In Figure 18 we see that the Delta-V reported by msmac3D in 2D mode for the vehicle-to-vehicle collision is 70.15 MPH. Note there are additional Delta-Vs of 6.1 MPH and 4.2 MPH that occur in the Buick and 4.4 MPH that occurs in the Tahoe. The EDR Delta-V logic for each vehicle is independent and does not try to match the DeltaVs of the colliding vehicles. The EDR only sees the vehicle acceleration of the vehicle in which it is mounted.

Note in Figure 19 the differences between the Delta-VRES (TEST EQUIVALENT) Delta-V and the DELATVACC (SMAC EQUIVALENT).

The reason for the differences is revealed by examining the right side of Figure 20 which is an enlargement of the scale for the Lateral (Y) acceleration. In Figure 20 we see the lateral acceleration (Y) oscillates from positive to negative G forces in many instances greater than 1 G-unit (which as previously mentioned is the on/off trigger for the start and end of the Delta-V calculations in msmac3D). It also produces large differences in the Delta-V if it is based on

the individual components (Delta-V-RES) instead of the resultant acceleration (DELATV-ACC). This anomaly is something that the EDR must deal with and should be the subject of another research project to determine: •

How do EDRs handle the fluctuations in the accelerations when calculating Delta-Vs?

For purposes of comparison with EDR data and determination of what might affect the results of the EDR outputs we will use the total Delta-V as determined by the smacTHP program for comparison with the EDR Delta-V data.

The second item to investigate: 2. Was the EDR anomaly due to limitations of the EDR data collection and the approximate 50 g limit?

As pointed out in the referenced article [2] EDRs may have a limit on the maximum acceleration that can be recorded during a collision interaction. This was also demonstrated

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Figure 19: smacTHP outputs for smac3D in 3D vs 2D mode showing the differences Delta-V calculations including TEST EQUIVALENT (Delta-V-RES) and SMAC EQUIVALENT (Delta-V-ACC), Maximum G’s and duration of collision

Figure 20: Accelerations of Tahoe (Veh1) and Buick (Veh2) in msmac3D Analysis in 2D mode.

On left is both Longitudinal (X) and Lateral (Y) accelerations and On right is a close up of the Lateral (Y) acceleration with range of +/- 1G-unit displayed 20 Collision Magazine - Volume 16 Issue 1

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Figure 21: NAPARS Crash Test Number 2 with EDR acceleration clipping and note the 50g indication on the EDR at the 2021 NAPARS conference in Crash test#2 previously mentioned where the indicated 50 G limit on the EDR (see right side of Figure 21] was in reality a 53.5 G limit (see left side of Figure 21 circled flat spot).

•

In a review of the acceleration time histories for the subject crash [Figure 6] there appears to be a limit of the maximum acceleration of approximately 44 G’s. To test the effects of implementing a 44 G limit we added an option to smacTHP to limit the Maximum G-force for the post processing Delta-V calculations [12].

The use of a maximum acceleration limit of 44 Gs helps explain one of the reasons for the difference in the EDR Delta-V compared with the theoretical amount based on the Tahoe Delta-V. But it doesn’t explain all the difference.

Note the maximum acceleration limit is ONLY in the integration of the accelerations to calculate the Impact Speed Change (Delta-V).

A comparison of the results is presented in Figure 22 through Figure 24: Figure 22 through Figure 24 demonstrate that limiting the post-processing maximum accelerations for the Buick to 44 Gs reduces the calculated Delta-V: •

The 44 G EDR limitation reduces the calculated Delta-V from 71.3 MPH (right side of Figure 22) to 59.3 MPH (Left side of Figure 22)

The post processing integration of the acceleration results in a Delta-V which is less than the actual by 12 MPH (17% less than actual). This helps explain some of the EDR anomaly.

Before moving on we also ran the Delta-V calculations while using the labeled 50 G maximum acceleration vs the actual measured 44 G maximum acceleration limit of the EDR to quantify what difference changing the limit by 6 Gs would make.

The results of the test of 44 Gs v 50 Gs limit are presented in Figure 25. The 6 G difference in the maximum acceleration leads to an approximate 5 MPH difference. In Figure 25 the value on left vs value on the right demonstrates an approximately 8 % difference in the Delta-V calculations if a 50 G v a 44 G limit were used. Care must be exercised in determining the actual maximum recorded value.

As we saw in the NAPARS test [Figure 21] the 50 G limit for that vehicle meant 53.5 Gs maximum acceleration whereas in this case the 50 G limit indicates approximately

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Figure 22: Summary of Delta-V calculations integrating the msmac3D accelerations limited to 44 Gs v no accel limit Delta-V Calculation

Figure 23: Comparison of EDR accelerations with msmac3D with and without a 44 G acceleration limit 22 Collision Magazine - Volume 16 Issue 1

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44 Gs. In either case the EDR data limitation will make the EDR calculated Delta-V lower than the actual DeltaV. However, it does not explain all of the reasons for the difference.

The next item to determine, in combination with the EDR limit, was: 3. Was the EDR anomaly due to some issue or limitation in the EDR Delta-V calculation logic?

Figure 24: Comparison of EDR Delta-V v msmac3D and msmac3D with 44 G limit

Figure 25: Comparison of Delta-V calculations for 44 G v 50 G maximum limitation www.collisionpublishing.com

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Might any offset of the EDR from the Center of gravity (CG) of the vehicle have an influence on the calculation of the Delta-V? What is the EDR logic for the start and end time for the integration of the accelerations to calculate the Delta-V and might it provide further explanation for the EDR issue??

EDRs are rarely located at the CG (Center of Gravity) of a vehicle due to the many variations in the vehicle build configurations and vehicle loading. Most have internal logic or adjustments to compensate for any changes which might result. In the RICSAC-97 paper [10] we found that accelerometers at locations other than the CG could result in very different Delta-V results.

For this subject case the collision is mainly longitudinal and the EDR only measured in the longitudinal (X) and lateral (Y) directions. We ran a few tests of the simulation with the EDR offset from the CG by up to 2 feet and found very little change in the Delta-V calculations due to the longitudinal configuration of the subject crash. We will leave an investigation of what, if any, changes may result in different loadings and/or different offsets of the EDR from the CG to another time and for another crash test which has significant yawing during the collision interaction.

For the subject crash the smacTHP program can be used to test variations of the start and end times for the impact speed change calculations.

If we examine a comparison of the accelerations of the EDR and the msmac3D simulation [Figure 26] we see that the EDR starts at a time after the start of the simulation acceleration.

The Delta-V calculation procedure for the msmac3D simulation program for a given acceleration exposure is determined by the integration of the resultant acceleration.

For each millisecond time increment during a collision, a resultant acceleration is determined by the vector sum of the x and y components of the vehicle accelerations. The SMAC/smacTHP logic assumes a collision occurs when the resultant acceleration of a vehicle goes above 1 G-unit and the collision ends when the acceleration of a vehicle goes back below 1 G-unit. It is not known what the logic is for the EDR (and it may vary by manufacturer and between models).

As a test of whether or not the differences in the EDRreported Delta-V might be due to both the Maximum G limitation and also possibly a difference in the start and

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end times for the Delta-V calculations, we determined the approximate start and end time for the EDR acceleration that would be considered a collision as the red arrows indicate in Figure 26 as: •

EDR Delta-V integration •

Start time 1.557 second where the EDR acceleration recording start

•

End time 1.615 seconds where the EDR acceleration abruptly reverses sign.

When we rerun smacthp to calculate the Delta-V with the approximate EDR start and end times determined above the results start to compare more favorably with the EDR data for the Buick [see Figure 27 through Figure 29].

•

The 44 EDR G unit limitation combined with the approximate start/end times observed from the EDR acceleration traces reduces the calculated Delta-V from 71.3 MPH to 48.7 MPH

•

48.7 MPH compares more favorably with the reported Delta-V for the Buick where the EDR reported between 45.3 to 46.6 MPH

We also looked at the start and end times for the accelerations of the Tahoe in the subject crash. See the EDR acceleration data for the Tahoe in Figure 12. The start and end times appear complete and correspond with the msmac3D acceleration start and end times.

The last item to review is: 4. Was the EDR anomaly due to the EDR proximity to the crash zone and movement during the crash?

Currently movement of an EDR during a collision interaction is not something that is modeled with crash simulation software. The movement, as pointed out in the article, was due to the engine displacement under the passenger compartment which produced a lifting and lateral shift of the EDR location during the crash interaction.

To model the effect of the movement would require a detailed 3D measurement of the final EDR location relative to an exemplar measurement of the initial OEM EDR location. Then there would have to be an assumption and approximation of the timing of the movement and the effects determined. To do such a research project is beyond the scope of this preliminary initial investigation.

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Figure 26: Comparison of EDR accelerations with the msmac3D reconstruction note the different start and end time for the EDR trace

Figure 27: EDR Delta-V Calculation v Baseline msmac3D v msmac3D with 44 G limit and adjustment of start/end time of Delta-V calculations www.collisionpublishing.com

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Figure 28: msmac3D smacthp post processing with 44 G limit and limit on start/end time for Delta-V Calculations

Figure 29; Comparison of EDR data, msmac3D crash simulation normal, then with 44 G limt and the 44 G limit with start/end time limits

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Summary A high speed crash test was presented in detail in Volume 15, Issue 2 of Collision Magazine. In the crash, documented EDR results had some anomalies which we have investigated. We found that the maximum G-limit of EDRs combined with adjustment of the start and end time of the Delta-V calculations to try to mimic the EDR software explains the main reasons for the anomaly in the EDR data and reports.

This article demonstrates that the interpretation of EDR results can be supplemented by the application of 3D simulation, such the msmac3D program. It is possible with computer simulation to supplement partial EDR results, to compare predicted and measured EDR time-histories and to test theories on data issues with EDRs. EDRs are NOT infallible, and they only make up a part of the data required for a complete crash investigation and reconstruction.

As a result of this preliminary investigation we have also performed an initial investigation of mimicking EDR integration algorithms to further help explain and understand EDR anomalies. We plan to publish on that topic soon.

A few additional research projects combining simulation and EDR data we plan to undertake include testing the time history waveforms produced by range limitations on accel­erometer readings, effects of tire-terrain friction values and corresponding vehicle/ground forces on EDR data, accel­erometer (EDR) positions and potential offsets and move­ments during collision interaction and further exploration of the effects of pitch and roll movements on EDR data.

References 1. See Title 49 of the Code of Federal Regulations, part 563 (49CFR563), "Event Data Recorder."

2. "Did you find any errors when you read through the data?," W. R. Rusty Haight & David W. Sersen, Collision Magazine, Volume 15, Issue 2, case problem.

3. FSR – "Front, Side and (or) Rear" events as defined in the La Crosse and the Tahoe Data Limitations 4. From the Data Limitations test: "The GM parameter name is displayed in parentheses after the NHTSA Part 563 parameter name." In other words, in this case, 49CFR563 calls for the data element "Maximum Delta-V, Longitudinal" and GM has added, paren¬thetically, their historical/typical name for this

element "Maximum Longitudinal SDM Recorded Vehicle Velocity Change for FSR Event)."

5. There is a corresponding "Maximum Lateral" Delta-V and time to that Maximum Lateral Delta-V, however, for this analysis, the translated value of -2 mph (-3 km/h) isn't terribly significant.

6. “A Review of the Development and Validation of Simulation Technology for Vehicular Accident Reconstruction”, Brian G. McHenry, McHenry Software, Dec 2015, Collision Magazine, Volume 10, issue 2 7. "A Short History of Nearly Everything! (...about McHenry and Computers in Highway Safety)", Brian G. McHenry, Collision magazine Volume 6, Issue 2 Fall 2011 8. “SMAC2003 - The Automatic Iteration of SMAC”, McHenry & McHenry, SAE 2003-01-0486 9. “In collisions why does Mass1DeltaV1 not always equal Mass2DeltaV2? ” McHenry Forum (https://www. mchenrysoftware.com/board) Topic 10. “RICSAC-97 A Reevaluation of the Reference Set of Full Scale Crash Tests”, McHenry & McHenry, SAE paper 97-0961 11. Tracker Video Analyis and Modeling Software https:// physlets.org/tracker/ 12. “Some EDRs have max accel limits, msmac3D can mimic that for direct comparison”, McHenry Forum (https://www.mchenrysoftware.com/board) Topic Acronyms Used in this Article ACM – Airbag Control Module CG - Center of Gravity DeltaV – Impact Speed Change DELTAV-ACC - SMAC EQUIVALENT DeltaV DELTAV-RES - TEST EQUIVALENT DeltaV EDR – Electronic Data Recorder FSR - Front Side and Rear HVOSM - Highway Vehicle Object Simulation Model Msmac3D - McHenry SMAC 3 Dimensional NAPARS – National Association of Professional Accident Reconstruction Specialists OEM - Original Equipment Manufacturer PDOF - Principal Direction of Force SDM - Sensing Diagnostic Module SMAC Simulation Model of Automobile Collisions smacTHP – SMAC Time History Program

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Analysis of the Event Data Recorder Information Obtained in Crash Testing of Supported and Pre-Supported Hyundai Vehicles: a 2015 Elantra Sedan and a 2012 Genesis Coupe Robert Anderson

Wesley Vandiver

Biomechanics Analysis, LLC

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Collision Forensics, Inc.

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A

bstract Hyundai and Kia automobiles have Event Data Recorder (EDR) functionality to record crashrelated data. The authorized distributor for the Global Information Technologies (GIT) America, Inc.’s EDR tool is available through Crash Data Group, which is also the authorized distributor for the Bosch CDR and Tesla EDR tools. Although the GIT EDR tools support Hyundai and Kia automobiles back to the 2013 model year, prior research has demonstrated that the GIT EDR tool can be used to obtain a copy of the EDR from most Hyundai and Kia automobiles back to the 2010 model year. However, using an EDR tool to obtain crash data from automobiles that are outside the supported model years, raises concerns that some or all of the EDR data has been properly translated.

This research expands upon a previous crash testing that was conducted as part of the Southwestern Association of Technical Accident Investigator’s (SATAI) 2020 Crash Conference. The prior crash testing investigated the appropriateness of the translation of speed and service brake status EDR data from a pre-supported Hyundai Genesis.

As part of the 2021 SATAI crash program, the Genesis was subjected to two additional head-on collisions and GIT EDR supported Hyundai Elantra was subjected to 16 front and rear crash tests, while speed, service brake status, and additional parameters such as longitudinal and lateral vehicle acceleration and Delta V, and steering wheel angle were measured or observed to compare with that reported in the post-crash EDR report.

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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 is 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 563 [1] (49CFR563 which may also 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.

Prior to the September 1, 2012 deadline, some manufacturers installed EDRs in their vehicles but had no publicly available tool for accessing and retrieving this data.

Kia and Hyundai, companies that share product development, were among these manufacturers. Prior research has shown that data from Kia and Hyundai vehicles may be retrievable dating back to model year 2010 for certain models. [2] In 2012, Global Information Technologies (GIT) America, Inc., a supplier of diagnostic tools for Hyundai, announced it was offering for sale the Hyundai and Kia EDR kits. The timing of this release corresponded with 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. While the 2015 Hyundai Elantra sedan was manufactured after 2013 and it is GIT EDR supported, the 2012 Hyundai Genesis Coupe was manufactured prior to the provisions of Part 563 taking effect. Therefore, the requirements of Part 563 do not apply to the EDR installed in the Genesis. However, Genesis ACM does have EDR functionality and its EDR can be accessed using the same direct-to-module cable designated for use with the EDR from a 2013 Hyundai Genesis Coupe, which is subject to the provisions of Part 563. Noteworthy, however, is the fact that a keyway on the module must be shaved away for the direct-to-module cable to be used.

When using the most current software version of the GIT tool for Hyundai EDRs, a vehicle identification number (VIN) from a 2012 vehicle cannot be used. At start-up, the software displays the following disclaimer:

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Figure 1: Hyundai EDR Tool software disclaimer Access to the EDR from a 2012 Hyundai Genesis Coupe can be had using the same hardware as would be used for a supported 2013 Hyundai Genesis Coupe. The only change required to gain access to the data is to enter a VIN into the software that is listed as being from a supported vehicle – in other words, a VIN from a 2013 or later Hyundai. It is, of course, recommended that the VIN used correctly identify the model vehicle under examination. For the purposes of this research, EDR downloads were obtained from the 2012 test vehicle by entering its actual 17-character VIN with only the year character (10th character) changed from “C” to “D.” Although this change would otherwise invalidate the VIN in terms of its check digit verification, it is accepted within the software as representing a supported 2013 Hyundai Genesis Coupe.

Literature Review Lawrence et al. [3] compared three different 2002 GM vehicles' pre-crash speeds to 5th wheel data at various speeds. They concluded that the pre-event 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. [4], 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 mph. Some of the differences in pre-crash vehicle speed data between the GM SDMs and reference instrumentation have been attributed to asynchronous data reporting, reporting resolution, rounding or cropping of reported data or wheel slippage during acceleration or braking [5].

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A 2008 Ford Focus and 2008 Ford Edge restraint control module (RCM) showed a maximum error between a VBOX reported speed and an RCM EDR recorded speed of −1.1 kph (−1.3%) and −0.9 kph (−1.1%), respectively.

The EDR reported pre-crash in 0.5 second increments, the accelerator pedal generally matched that reported on the CAN bus, and the average delay or latency for a change in brake switch status was 0.41 or 0.42 seconds [6].

stant speed operation. Brown et al. [12] provided data plots for pre-crash vehicle and engine speeds for a 2011 Toyota Camry, a 2010 Toyota 4Runner and a 2011 Toyota Prius. They concluded that the Toyota EDR pre-crash data and other parameters were accurate when compared with the HS-CAN data; however nominal error rates were not reported. Ruth et al. [13] reported errors for a 2010 Toyota Camry EDR pre-crash speed under steady-state conditions within +0.4 to −2.3 kph of the referenced GPS Ruth and Daily [7] also studied a 2010 Ford Flex dur- instrumentation. At 113 kph, the differences equated to ing steady-state and braking conditions. They found that +0.4%/−2.0%. They also reported error for a 2011 Toyota under steady-state conditions the RCM EDR average un- Camry EDR pre-crash speed under steady-state conditions derreporting error in speed was 1.4% and that the 99% to be +0.0 to −3.0 kph of the referenced instrumentation. confidence interval was within 2.5% at 113 kph. As previ- At 113 kph, the differences equated to +0/−2.7%. A comously reported, the average reporting error increased dur- parison of J-NCAP EDR pre-crash velocity and the reporting deceleration due to the expected wheel slip during the ed test velocity for 14 Toyota models was performed by hard braking maneuver. The EDR reported accelerator Takubo et al. [14]. In all cases the difference was less than pedal tracked the CAN bus value, but due to being re- 7% with an average of approximately 2% and root mean ported with less precision was accurate within 0.5%. The square of approximately 3%.

EDR reported pre-crash in 0.5 second increments, and the time between pedal contact to when the EDR reported In 2013, Diacon, Ruth and Mueller [15] tested and rebrake on was relatively uniformly distributed between 0.05 ported on the accuracy of vehicle speed reported by EDRs and 0.5 seconds. in a 2012 Honda CR-V and 2012 Honda Civic. The vehicle speed data from the CR-V EDR, when compared Ruth and Reust [8] reported on the accuracy of two Chrys- to a VBOX, under conditions of moderate acceleration ler ACM EDRs. The 2008 Jeep Commander ACM EDR and braking was +/- 1.15 kph with a mean of +0.033 kph speed data was within 1.5% of the VBOX data using a 3 and a standard deviation of 0.39 kph. Under steady state sigma statistical criteria. The 2008 Dodge Dakota ACM conditions the 2012 Civic vehicle speed CAN bus mesevent data was reported to be within −3.1 kph or −2.7% sage (speed, vehicle indicated) accurately represented the of the reference VBOX speed at highway speeds. At low- vehicle ground speed. The EDR truncated the CAN speed er speeds, the absolute error was less but the percentage to the next lower whole kph, resulting in the average GPSwas higher. The error averaged approximately −2% of the EDR difference being higher by approximately 0.5 kph, speed being traveled. The EDR reported accelerator pedal to a mean of +0.22 kph with a standard deviation of 0.33 position matched the pedal sensor output within 3.2% kph. The range was from −1.38 kph to +1.95 kph. This and the brake switch on was reported on the CAN bus corresponds to accuracy within about 2% at speeds near within hundredths of a second. The largest delay or la- 100kph as tested with new, minimally worn tires. tency between when the brake switch is tripped and when brake on is reported in EDR data is due to time interval to In 2013, Vandiver, Ikram and Randles [16] tested the acthe next EDR sample. curacy of pre-crash speed recordings in a 2009 Mitsubishi Lancer GTS. They used a 4-wheel dynamometer to alBortolin et al. [9] reported an average error of 1.11 mph low for the testing of accuracy under hard acceleration at and maximum error of 1.74 mph during steady state speed speeds over 85 mph. When compared to the dynamomfor a 2008 Dodge Grand Caravan. eter, the Mitsubishi EDR tended to slightly overreport the The controller area network (CAN) data for a Mini Coo- vehicle speed by an average of 4.34%, but closely matched per was shown to overreport vehicle speed by as much as the speed being reported by the vehicle speedometer.

3.7 kph at low speeds and under report by as much as 4.34 kph at higher speeds [10]. Mueller at al. concluded that the Mini Cooper reported wheel speed was approximately 5% higher than the VBOX without heavy braking.

Testing of a 2010 Toyota Camry by Brown and White [11] indicated that the High-speed CAN (HS-CAN) speed data was less than the actual speed by 2.7% during con-

In 2013, Haight, Gyorke and Haight presented examples of crash related data obtained from both supported and unsupported Hyundai ACMs using the commercially available GIT Hyundai/Kia EDR tools. It was shown that different data translations could be obtained depending on the year, make or model that was entered to access the crash record. The authors concluded that end users would

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not normally have a way to verify which part or parts of the translation were correct. [17] In 2014, Ruth and Tsoi [2] tested the accuracy of EDR translations from 2010-2012 Kia and Hyundai vehicles using the 2013 Hyundai and Kia EDR Tools manufactured by GIT. The data in these vehicles were accessed using various cables and by varying the year and model selections within the GIT software. A total of 56 ACMs were obtained from vehicles used in National Highway Traffic Safety Administration (NHTSA) New Car Assessment Program (NCAP) tests. Of those, 54 were able to be read and compared to data collected and documented in the testing reports published via NHTSA. The emphasis of this research was the accuracy of speed and Delta-V data due to the lack of data generated during the NHTSA testing related to other elements, including braking, engine rpm, throttle position, Anti-lock Braking System (ABS) activation, stability control and steering input. In 20 of 22 frontal tests examined, the reported speed was within ±4%.

In Test 7612, involving a 2012 Kia Soul, the speed was underreported by -3.42 kph, a difference of -6.1%. The readings for longitudinal Delta-V in 20 of the 22 frontal tests were accurate to within -8% to +14% of reference and 19 of those 20 were within the ±10% normally ascribed to benchmark GM EDR Delta-V data (excluding clipping).

Lateral Delta-V reported in the EDRs from side Moving Deformable Barrier (MDB) and side pole tests was generally proportional to reference, but several EDR data points reported outside the normal ±10% range.

In 2015, Vandiver, Anderson, Ikram, Randles, and Furbish [18] tested and examined the accuracy of the crash data recorded in a 2012 Kia Soul, which was also one year too old to be officially supported by the GIT Kia EDR tool. Although the testing regimen used in that research included different types of tests, the data collection and analysis methodology were largely similar to that used in this research. Vandiver, et al. [18] found that the reported pre-impact speed, steering angle, engine speed, and brake switch status compared favorably with the data from the test instrumentation.

From the research preceding the current study, Vandiver & Anderson reported in 2021 that the accuracy of EDR reported speed and service brake status from the 2012 Hyundai Genesis, which was also one year too old to be officially supported by the GIT Hyundai EDR tool was found to be properly recorded and retrievable using the GIT EDR tool. [19]

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Test Vehicles The Hyundai Genesis test vehicle for this research is pictured in Figure 2.

Figure 2: The Pre-GIT EDR supported 2012 Hyundai Genesis The bullet vehicle used for the pre-supported Hyundai crash tests in this research was a 2012 Hyundai Genesis Coupe 2.0T R-Spec with VIN KMHHT6KD2CU067432, which was rear-wheel drive and equipped with a 6-speed manual transmission. The vehicle weight without the 200-pound human driver was measured to be 3193 pounds using Longacre DXI scales. The ACM for the test vehicle was installed along the center tunnel of the vehicle as depicted in Figure 3.

Figure 3: Hyundai Genesis’s ACM location on the center tunnel The target vehicle used for both head-on crash tests was a stationary 2005 Chevrolet Astro cargo van, shown in Figure 4, with VIN 1GCDM19X35B129423, which was rear wheel drive and equipped with an automatic transmission, which weighed 3910 pounds according to Expert Auto-

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stats®. The vehicle weight was confirmed to be 3910 using Mass Load scales.

Figure 4: The Astrovan target vehicle for the head-on crashes

Figure 6: Hyundai Elantra’s ACM location on the center tunnel under the center stack

Figure 5: The GIT EDR tool supported Hyundai Elantra

Figure 7: The Chevrolet Sonic collision partner for the Elantra crash tests

The GIT EDR tool supported test vehicle was a 2015 Hyundai Elantra, VIN 5NPDH4AE4FH613424, shown in Figure 5. It is a four-door sedan with frontal wheel drive and an automatic 6-speed transmission. The ACM was on the center tunnel beneath the center stack as shown in Figure 6. The vehicle weight was 2661 according to Expert Autostats®. Without the 200 pound human driver and the passenger doors removed, the test vehicle with instrumentation and two ATD’s was weighed to be 2950 pounds using Mass Load scales.

Equipment & Instrumentation

The collision partner for the Elantra in all 16 crash tests was a 2015 Chevrolet Sonic LT, VIN 1G1JC6SB7F4149884 shown in Figure 5, which was a 4-door hatchback with front wheel drive and a 6-speed automatic transmission.

The vehicle weight according to Expert Autostats® was 2684 pounds. The vehicle weight with the passenger doors and only the instrumentation installed (no ATDs), the vehicle weight was measured to be 2690 pounds using Mass Load scales.

The Hyundai Genesis was instrumented with DTS TDAS Pro rack with four 8-channel Signal Input modules. The TDAS recorded data at 10,000 Hz. The TDAS collected analogue speed output from a Racelogic VBOX 3i, which collects, calculates and records speed at 100 Hz based upon the doppler shift of GPS satellite radio signals. When averaged over four samples, the reported accuracy is ± 0.06 mph for speeds up to 1000 mph. The TDAS also collected human subject accelerations, seat belt loads, as well as vehicle acceleration and rotation data from accelerometers mounted near the vehicle’s center of gravity on the ACM, string potentiometers wrapped around the steering column for steering wheel angle and on the brake for brake pedal displacement, and well as a brake pedal load cell, and an airbag current sensor, should a deployment occur.

Video of the two head-on crashes between the Genesis and the Astrovan was obtained from a ground based high speed

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and real time cameras, Garmin Virb cameras on both vehicles, and from an aerial drone.

For data collection from the Hyundai’s EDR, the Hyundai GIT EDR Tool was used with the most current version of the software available on the date of the tests (version E-NH-01-00-0037). For the purpose of EDR downloads using the GIT EDR tool, a VIN of KMHHT6KD2DU067432 was entered.

The Hyundai Elantra was instrumented with DTS Slices housed in custom 16 channel racks which collected data from a triaxial accelerometer mounted on the ACM, as shown in Figure 6, as well as ATD accelerations, moments, forces and displacements at 10,000 Hz. Video of the Elantra versus Sonic crashes was obtained with Video VBOX HD’s. This system collects GPS data for location and speed and allows for the 1080p video from one or two cameras to be synced with the collected data. The Video VBOX HD collects, calculates and records speed at 10 Hz based upon the doppler shift of GPS satellite radio signals. When average over four samples, the reported accuracy is ± 0.06 mph for speeds up to 1000 mph. Video of the crashes between the Elantra and the Sonic was obtained from on-board and ground based high speed and real time cameras, Garmin Virb cameras on both vehicles, and from an aerial drone.

driver steered side-to-side before straightening up and hard braking at an approximate location that was estimated to result in an impact speed of approximately 25 mph with the front of the stationary Astrovan target vehicle.

The Elantra was human driven into the rear of the stationary Sonic target vehicle in 12 crash tests with planned impact speeds within the 6 to 30 mph range. The Elantra was also driven into the passenger side of the Sonic in an angled broad-side type contact in two crash tests and the Sonic was driven into the left front of the stationary Elantra in two crash tests.

The 2012 Hyundai Genesis Coupe Crash Test Results The pre-GIT EDR supported Hyundai Genesis was human driven into the stationary Chevrolet Astrovan in two head-on crashes at 22.9 mph and 24.8 mph. Each crash triggered a new EDR event to be recorded as Event 1 replacing the previously recorded Event 1 without recording any events as Event 2.

The ignition cycles advanced between EDR downloads consistent with the handling of the vehicle. The seat belt buckle status of the driver was correctly reported as buckled and the front passenger seat belt buckle status was reported as not supported.

The airbag warning light was not illuminated and there were not any deployments produced in the Hyundai Crash Tests Genesis crashes. However, in the EDR reports the airbag The Genesis was driven using a seat belted human driv- warning light was reported to be “on”, and deployment er around the track in order to obtain pre-crash speeds times were listed for the frontal 1st and 2nd stage airbags, within the approximate 30 to 45 mph range. This was side airbags and curtains, and front pre-tensioners. In adaccomplished by driving in a loop around the track, while dition, complete file recorded was reported to be “no” and accelerating and shifting gears. The layout of the track invalid data or not supported was indicated for ABS, Staallowed for a linear path into the eventual impact. The bility control and Steering, as shown in Figure 8.

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For the first head-on collision with the Pre-GIT EDR supported Genesis, the comparison of EDR reported speed, service brake information and steering wheel angle and that measured with reference instrumentation is shown in Figure 9 through Figure 11 and the comparison of EDR reported longitudinal acceleration and Delta V, and lateral acceleration and Delta V are shown in Figure 12 through 15.

For the second head-on collision with the Pre-GIT EDR supported Genesis, the comparison of EDR reported speed, service brake information and steering wheel angle and that measured with reference instrumentation is shown in Figure 16 through Figure 18 and the comparison of EDR reported longitudinal acceleration and Delta V, and lateral acceleration and Delta V are shown in Figure 19 through 22.

Figure 9: First head-on crash EDR vs. VBOX speed

Figure 10: First head-on crash EDR brake on/off vs. pedal displacement

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Figure 11: First head-on crash EDR steering wheel angle vs. reference

Figure 12: First head-on crash EDR longitudinal acceleration vs. reference

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Figure 14: First head-on crash EDR lateral acceleration vs. reference

Figure 15: First head-on crash EDR lateral Delta V vs. reference

Figure 16: Second head-on crash EDR vs. VBOX speed www.collisionpublishing.com

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Figure 17: Second head-on crash EDR brake on/off vs. pedal displacement

Figure 18: Second head-on crash EDR steering wheel angle vs. reference

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Figure 20: Second head-on crash EDR longitudinal Delta V vs. reference

Figure 21: Second head-on crash EDR lateral acceleration vs. reference

Figure 22: Second head-on crash EDR lateral Delta V vs. reference www.collisionpublishing.com

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2015 Hyundai Elantra Crash Tests The GIT EDR supported Hyundai Elantra was subjected to 16 front and rear crashes. Each crash triggered a new EDR event to be recorded as Event 1 replacing the previously recorded Event 1 without recording any events as Event 2.

The ignition cycles advanced between EDR downloads consistent with the handling of the vehicle. The seat belt buckle status of the driver and front passenger was correctly reported as buckled or unbuckled. The airbag warning light was correctly reported as not illuminated. During the test series, the airbag warning light illuminated after the 6th impact and was correctly reported as on for the remainder of the test series.

Each recorded event was indicated to be complete. None of the pre-crash parameters were reported at invalid or not supported, except 3rd Stage frontal airbags deployment

times, and deployment times were not reported until the final crash when frontal airbags and seat belt pretensioners deployed.

The largest frontal and rear-end impacts that did not trigger an EDR recording had a -4.4 mph Delta V and +5.8 mph Delta V measured with the reference instrumentation. The smallest impact that triggered an EDR recording was a -6.3 mph delta-V impact, which had an EDR reported delta-V of -8 kph.

Although not instrumented, the EDR reported steering wheel angle appeared appropriate for the movement observed in on-board video.

The pre-crash speeds reported by the EDR compared to the reference VBOX speed are shown in Figure 23. The comparison between EDR reported longitudinal and lateral acceleration and Delta Vs are shown in Figure 24 through Figure 27.

Figure 23: EDR vs. VBOX Speed from Crash Test 16

Figure 24: Elantra EDR and Reference Longitudinal Acceleration from Crash Test 16 40 Collision Magazine - Volume 16 Issue 1

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Figure 25: Elantra EDR and Reference Longitudinal Delta V from Crash Test 16

Figure 26: Elantra EDR and Reference Lateral Acceleration from Crash Test 16

Figure 27: Elantra EDR and Reference Lateral Delta V from Crash Test 16 www.collisionpublishing.com

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Discussion Both GIT supported and pre-GIT supported Hyundai vehicles exhibited the same recording behavior in that each new event was recorded into Event 1’s memory location over-writing any prior recorded event. Crash test research with a pre-GIT supported Kia vehicle exhibited the same recording behavior. Consistent with Hyundai and Kia EDR reports from the authors’ case work, it appears that GIT EDR supported vehicles only record two events when those events are related or if a deployment event locks Event 1 in memory so that new events can only be recorded in the Event 2 memory location. This crash test program did not attempt to produce two related events.

The comparison between the EDR pre-crash and crash data from the GIT supported Hyundai Elantra and the reference instrumentation and observations is generally within that observed from other manufacturer’s supported vehicles. Perhaps this should be expected for post-part 563 automobiles.

For the pre-GIT EDR supported Hyundai Genesis the translation of pre-crash speeds and service brake information was again found to be properly translated. Ignition cycles and driver seat belt buckle status was also correctly translated.

However, for the pre-GIT EDR supported Genesis some of the parameters were reported to be invalid or not supported at discrete pre-crash times, raising concerns of improper translation and/or vehicle problems. The steering wheel angle, SRS warning light status, and presumably complete file recorded were not correctly translated.

The pre-GIT EDR supported Genesis’ reported longitudinal and lateral accelerations were not correctly reported indicating that these crash parameters were not correctly translated. As a result, the vehicle’s acceleration data could

not be integrated to obtain vehicle Delta Vs. In spite of the acceleration translation issue, the EDR reported longitudinal and lateral Delta Vs corresponded well with the reference instrumentation evidencing proper translation of these parameters.

It is noteworthy, that in these authors’ experience on rare occasion GIT supported vehicles can report unrealistic EDR parameters, such as the lateral acceleration shown in Figure 28. Certainly, it would not be proper to attempt to include this data in a situationally complete crash analysis.

The results of the pre-GIT supported testing shows how some EDR parameters can be properly translated while others are not. In the case of vehicle accelerations, it may not be obvious to visual inspection that there has been a mistranslation. This confirms the value of verification testing before adopting EDR data from an unsupported vehicle as representing the vehicle’s actual pre-crash and crash behavior.

In keeping with the concept that the most of frontal crash exposures of live humans has generally been limited to vehicle velocity changes of 20 mph or less, and the findings of R. Wagner, an Audi researcher, who concluded that vehicle velocity changes within this range were “safe” for live human exposures [20], the testing was planned and executed to produce vehicle velocity changes of less than 20 mph.

Conclusions Even though the EDR report form has space for Event 1 and Event 2, without related events or prior locked events, the Hyundai test vehicles were observed to only recorded one event at a time. This recording behavior is consistent with that observed in other GIT EDR supported test vehicles and those in the authors’ case work.

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The pre-GIT supported vehicle correctly translated precrash speed, service brake information, ignition cycles and driver seat belt buckle status.

The longitudinal and lateral Delta V was also correctly translated in the pre-GIT supported vehicle.

However, the steering wheel angle, SRS warning light, longitudinal and lateral acceleration are not reliable since they were not correctly translated.

The inaccuracy of EDR data due to mistranslation from un-supported vehicles underscores the importance of verification testing before adopting recorded parameters as representing the vehicle’s actual behavior.

The accuracy and behavior of the EDR data from the GIT supported vehicle was consistent with that which has become expected from the post-part 563 supported vehicles from other automobile manufacturers.

References 1.

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“49CFR563”; 49CFR563 – EVENT DATA RECORDERS. NHTSA, 1 Oct. 2011. Web. 13 Dec. 2014; http:// www.gpo.gov/fdsys/granule/CFR-2011-title49-vol6/CFR2011-title49-vol6-part563/content-detail.html

Ruth, R. and Tsoi A. “Accuracy of Translations Obtained by 2013 GIT Tool on 2010-2012 Kia and Hyundai EDR Speed and Delta V Data in NCAP Tests,” SAE technical paper 2014-01-0502, 2014, doi: 10.4271/2014-01-0502.

Lawrence, J., Wilkinson, C., Heinrichs, B. and Siegmund, G. “The accuracy of pre-crash speed captured by event data recorders,” SAE technical paper 2003-01-0889, 2003.

Bare, C., Everest, B., Floyd, D. and Nunan, D. “Analysis of pre-crash data transferred over the serial data bus and utilized by the SDM-DS module,” SAE technical paper 201111-0809, 2011, doi:10.4271/2011-01-0809.

Wilkinson, C., Lawrence, J., Heinrichs, B. and King, D. “The timing of pre-crash data recorded in General Motors sensing and diagnostic modules,” SAE technical paper 2006-01-1397, 2006.

Ruth, R., West, O. and Nasrallah, H. “Accuracy of selected 2008 Ford restraint control module event data recorders,” SAE technical paper 2009-01-0884, 2009.

Ruth, R. and Daily, J. “Accuracy of event data recorder from 2010 Ford flex during steady state in braking conditions,” SAE technical paper 2011-01-0812, 2011, doi: 10.4271/2011-01-0812.

Ruth, R. and Reust, T. “Accuracy of selected 2008 Chrysler airbag control module event data recorders,” SAE technical paper 2009-01-0877, SAE Int. J. Passeng. Cars – Mech Syst., Volume 2, Issue 1, 2009.

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Bortolin, R., Gilbert, D., Gervais, J. and Hrycay, J. “Chrysler airbag control module (ECM) data reliability,” SAE technical paper 2010-01-1002, 2010.

10. Mueller, C., Daily, J. and Papa, M. “Accessing the accuracy of vehicle event data based on CAN messages,” SAE technical paper 2012-01-1000, 2012, doi:10.4271/2012-011000.

11. Brown, R. and White, S. “Evaluation of Camry HS-CAN pre-crash data,” SAE technical paper 2012-01-0996, 2012, doi:10.4271/2012-01-0996.

12. Brown, R., Lewis, L., Hare, B., Jakstis, M., Landis, R., Clyde, H. and Buetzer, R. “Confirmation of Toyota EDR pre-crash data,” SAE technical paper 2012-01-0998, 2012, doi:10.4271/2012-01-0998.

13. Ruth, R., Bartlett, W. and Daily, J. “Accuracy of event data in the 2010 and 2011 Toyota Camry during steady-state and braking conditions,” SAE technical paper 2012-010999, SAE Int. J. Passeng. Cars – Electron. Syst., Volume 5, Issue 1 (May 2012), 2012, doi:10.4271/2012-01-0999.

14. Takubo, N., Hiromitsu, T., Kato, K., Hagita., Oga, R., Kihira, M. and Yamasaki, T. “Study on characteristics of event data recorders in Japan; analysis of J-NCAP and 13 crash tests,” SAE technical paper 2011-01-0810, 2011, doi:10.4271/2011-01-081.

15. Diacon, A., Daily, J., Ruth, R., and Mueller, C., “Accuracy and Characteristics of 2012 Honda Event Data Recorders from Real-Time Replay of Controller Area Network (CAN) Traffic,” SAE Int. J. Trans. Safety 1(2):399-419, 2013, doi:10.4271/2013-01-1264.

16. Vandiver, W., Ikram, I., and Randles, B., “Accuracy of PreCrash Speed Recorded in 2009 Mitsubishi Lancer Event Data Recorders,” SAE Technical Paper 2013-01-1263, 2013, doi:10.4271/2013-01-1263.

17. Haight WR, Gyorke S & Haight S, “Hyundai and Kia Crash Data, The Indispensable Compendium,” Collision Magazine, Vol 8, Issue 2 – Fall 2013.

18. Vandiver, W., Anderson, R., Ikram, I., Randles, B. et al., “Analysis of Crash Data from a 2012 Kia Soul Event Data Recorder,” SAE Technical Paper 2015-01-1445, 2015, https://doi.org/10.4271/2015-01-1445.

19. Vandiver, W., and Anderson, R., “Analysis of Crash Data from a 2012 Hyundai Genesis Coupe Event Data Recorder,” SAE Technical Paper 2021-01-0905, 2021, https://doi. org/10.4271/2021-01-0905.

20. Wagner R, “A 30 mph Front/Rear Crash with Human Test Persons,” SAE paper 791028, Proceedings of 23rd Stapp Car Crash Conference, Society of Automotive Engineers, 1979.

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PR OB LE M

Verifying EDR Data

CA SE

from a Ram ProMaster 1500 Van Collision Chris Medwell, PE

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I

ntroduction In most EDR data training classes, one of the themes you will hear from the instructor is: check and verify the EDR data. For example, we are taught to verify speedometer calibration by checking that the tire size on the vehicle is close to that programmed into the vehicle electronic system. Verifying also includes comparing the EDR data to other sources of the same information. To the extent possible, you should reconstruct the crash using crash physics like momentum or damage energy, to ensure the EDR data you plan to rely on is from the crash you are investigating and comports with the crash physics. If you have two EDR data records from vehicles that collided with each other, you should check whether the impact force on one vehicle roughly matches the impact force on the other [1]. If there is video footage of the crash you should check if the EDR data matches the video. Even though witnesses are often wrong about what they think they saw, you should compare the data and your reconstruction to what drivers and witnesses say about the crash.

In short, you should compare the recorded EDR data with your “situationally complete” reconstruction calculations on both impact speed and ∆V to ensure that the data accurately reflects the crash physics so that no one can compare the facts of the crash to the data (or one aspect of the data to another aspect of the data) and say: “Wait, that doesn’t look right.”

But what if it does not look right? What if the EDR data seems wrong? What do you do then?

First, check your work. Then, check it again.

Compare weights to specification sheets from more than one source. Vary your approach and/or departure angles by any reasonable values. Check the speed through other means. Do you have engine RPMs? Check if the vehicle can go that speed at that RPM. What gear would it have to be in?

Does that comport with your other information?

In most cases, if you cannot rationalize the EDR data to the reconstruction, it is going to be something wrong with the reconstruction or perhaps something wrong with the particular vehicle involved in your crash, as we theorized in the present case. Only in our case, we ended up discovering not something wrong with the crash vehicle, but something amiss with the OEM translation of the EDR pre-crash data. www.collisionpublishing.com

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Background Bloomberg Consulting was retained to investigate and reconstruct a fatal collision involving a 2018 RAM ProMaster 1500 cargo van and a HarleyDavidson motorcycle. The reported facts were that the motorcyclist had stopped in the roadway at an intersection, intending to make a left turn. While stopped, the motorcycle was struck from the rear by the van and propelled a minimum of 50 ft. (See Figure 1).

Figure 1: Scene photograph showing van and motorcycle at final rest The van driver braked to a stop after the collision and came to rest behind the motorcycle and rider.

The van driver told the police that she did not see the motorcycle. The speed limit on the roadway was 55 mph and witnesses told the police that the van appeared to have been going about 55 mph and did not apparently slow down before the collision.

Below is an outline of the facts developed during the initial investigation, to be used in solving this case problem: CDR Data The CDR data report from the van contained a non-deployment (ND) event record which indicated that the van had sustained a longitudinal ∆V of -6.8 mph in the collision. (See Figure 2).

The Pre-Crash Data (5 seconds recorded at 10HZ) indicated that the van had been traveling in a steady-state condition for nearly the entire 5 s, with the recorded speed at 19-20 mph, the accelerator pedal at about 10%, and the engine at just under 1700 RPM. The driver braked about ½ sec-

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Figure 2: Bosch CDR (Version 17.9.1) Longitudinal Delta-V chart (2018 RAM ProMaster 1500 Van) ond before the impact and the last recorded speed was 18 mph. (See Figure 3).

RAM ProMaster 1500 Cargo Van The ProMaster was new to the US in 2013, but the van was actually the US version of a front wheel drive van sold in Europe since 2006 as the Fiat Ducato/Citroën Jumper/ Peugeot Boxer. The European versions all had diesel (or CNG) engines, but the ProMaster offered in the US was equipped with Chrysler’s 3.6L Pentastar V6, a gasoline engine available in numerous other Chrysler products stateside (e.g. minivans). So, engineers at Fiat Chrysler Automobiles (FCA) in the US had to adapt this existing European van to utilize American engines, transmissions, and airbag control systems.

The van involved in the subject collision was a 2018 Ram ProMaster 1500 High Roof cargo van with a listed curb weight at 4776 lb. The van was empty but for the driver, who was an adult female of unknown weight. The van had less than 4000 miles on it at the time of the collision and it was not modified from its factory configuration; its tires were LT225/75R16, the same size as the original tire size listed on the Tire and Loading Information placard affixed to the vehicle. Specifications for the ProMaster transmission are: 6-speed automatic 62TE, final drive ratio 3.86, 1st gear ratio 3.90, 2nd 2.69, 3rd 2.16, 4th 1.37, 5th 0.95, 6th 0.65.

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Harley-Davidson FLS motorcycle The motorcycle involved was a 1998 FLSTC Heritage Soft Tail Classic with a dry weight of 690 lb. The rider was an adult male of average height and weight. No passengers or significant cargo were on the motorcycle.

The Roadway The diagram from the crash report is reproduced in Figure 4.

The crash occurred in a rural area on a 2-lane state highway with a posted speed limit of 55 mph. The terrain was level and the roadway was straight with pavement in good condition. A photograph (taken by police) showing the van at final rest is shown in Figure 5. Tire marks visible in the photograph indicate maximum braking by the van driver to final rest. Repetitive gouges leading from impact to final rest indicated the path of the motorcycle as it was propelled ahead of the van.

Bloomberg Consulting determined that the distance from the point of impact to the final rest of the front of the van was a minimum of 50 feet. The motorcycle was propelled nearly 60 ft. Its rider was ejected during the collision and came into contact with the van’s windshield. The two vehicles came to rest with the motorcycle rider lying on the roadway in between them.

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Figure 3: Bosch CDR Pre-Crash Data table (2018 RAM ProMaster 1500 Van generated in the then-current copy of the software v17.9.1 During the analysis of the data, translation of the data using updated versions of the CDR Tool software were unchanged

Figure 5: Scene photograph showing impact area and van at final rest. Note the tire “shadow” marks leading to the wheels of the van. www.collisionpublishing.com

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Case Problem Assignment To repeat & emphasize once again: the type of analysis suggested in this assignment is something that you should routinely be doing on every case – it is part of verifying the EDR data as being both germane to your case and consistent with the physical evidence and with the physics of the collision. Most of the time, this type of analysis will verify the EDR data. But if something doesn’t look right, find out why.

Question 1: Calculate the post-impact speed for the van based on the CDR-reported column titled “Speed, Vehicle Indicated” of the van and its recorded ∆V. Use this postimpact speed to estimate the required post-impact braking distance for the van to come a stop after the collision.

Compare this distance to the 50 feet of maximum braking marks evident at the scene. What braking deceleration rate would be required for the van to take 50 feet to stop following this collision? Calculate the post-impact speed of the van if the van was in fact braking hard for 50 ft post collision.

Question 2: Calculate the ∆V for the motorcycle/rider combination based on the CDR-reported ∆V for the van.

Question 3: Calculate the expected impact speed for the van based on the motorcycle and van ∆V’s determined in Question 2. Does anything stand out about the result of these calculations?

Question 4: Assuming that the Pre-Crash Data reported within the (version 17.9.1) CDR report is correct, what gear would the van’s transmission have been in prior to the brake being applied?

Question 5: Based upon the results of the above exercise, do you see any issues with the CDR-reported data for this collision? "If there is an issue, how would you explain the apparent discrepancy?

See following pages for excerpts from the vehicle CDR report version 17.9.1

Footnote: [1] W.R. Rusty Haight, David W. Sersern, Did You Find Any Errors In The Data As You Read Through The Data? (Temecula, CA: Collision Magazine, Volume 15, Issue 2, 2021). pg. 10-11.

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Restitution, Impulse Space, and Orientations Micky Marine SSi Phoenix, Inc. 60 Collision Magazine - Volume 16 Issue 1

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R

estitution The notion of a coefficient of restitution is one related to the energy loss between colliding bodies.

In a collision, energy is dissipated through material plastic deformation as well as vibration, friction, internal material damping, etc. In general, the details of the energy loss processes are quite complex, and as a result, analysts turn to simplifying parameters like a coefficient of restitution to facilitate analyses. Dynamics textbooks often cover the subject of restitution in discussions of impulse-momentum methods within the context of smooth spherical objects impacting one another. This leads to the establishment of a convenient orthogonal coordinate system wherein one axis is parallel to the tangent at the point where the two spheres make contact, and the oth-

er is normal to this tangential axis and necessarily passes through the centers of mass of the colliding spheres. In the impact configuration depicted in Figure 1, the impulse between the spherical objects is considered to act normal to the surface tangents at the point of impact. To assist in characterizing the energy loss and restoration of the collision, a coefficient of restitution is employed, often as a ratio of the normal-component separation speed relative to the normal-component approach speed. Isaac Newton discussed this behavior, observed in experiments conducted with spheres striking one another, in his seminal work “The Mathematical Principles of Natural Philosophy” [1]; what is now widely known as a coefficient of restitution has also been referred to as Newton’s Experimental Law.

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The coefficient of restitution as an engineering parameter provides little fundamental information regarding the complexities of energy loss and structural recovery processes. Goldsmith [2] notes, in commenting on Newton’s Principia, “Newton not only furnished his laws of motion but also the notion of the coefficient of restitution, which is still widely employed, though of questionable fundamental significance.” Chatterjee [3] states, “The coefficient of restitution is a widely used dimensionless parameter for collision models. Its fundamental validity is doubtful. But it has a clear interpretation in terms of energy dissipation.”

Figure 1: Impact of Spherical Bodies Some frequently employed definitions of the coefficient of restitution for use in impact mechanics models include the kinematic relationship (Newton’s coefficient) mentioned above, defined as a ratio of the relative separation velocity to the relative approach velocity where the velocity components are resolved normal to the impact surface (see Figure 1):

(1)

A kinetic definition (Poisson’s coefficient) is based on the ratio of the restorative impulse (PR) relative to the compressive impulse (PC):

(2)

A third definition for the restitution coefficient is based on the ratio of the energy returned to the system by the normal force during rebound (ER) relative to the energy dissipated by the normal force during the compression phase (EC) (Stronge’s coefficient), expressed as follows:

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(3)

From Smooth Spheres to Automobiles In evaluating non-collinear, non-central automobile impacts, some have defined a kinematic coefficient of restitution wherein the pre- and post-impact velocity components are resolved along a line connecting the system center of mass of the collision partners [4, 5]. A fundamental problem can arise when using these definitions, however, that renders their use in anything other than central impacts questionable. Under certain collision scenarios the defined restitution values would necessarily have to be less than zero, despite the fact that energy restoration (i.e., positive restitution) is nonetheless occurring in the contact zone. A fairly obvious example of this is a front corner-tocorner, intersection-type impact configuration where, after the impulse has occurred, the centers of mass of the collision partners continue to move toward one another due to the angular velocity imparted to the respective vehicles.

For non-collinear, non-central impacts, an approach using rigid-body planar impact mechanics (PIM) concepts have been employed where the restitution is considered in the context of the interaction of the two vehicles at a userdesignated single point of interaction, called an impulse center (IC).

There have been several planar impact mechanics models discussed in the literature for use in automobile accident analyses. The impulse ratio model, discussed in a number of treatises by Brach, e.g., [6], and the slip ratio models presented by Ishikawa [7] (though Ishikawa refers to his slip ratio as a tangential restitution) and Smith [8] employ a kinematic coefficient of restitution applied to the relative normal velocity components, calculated at the IC, normal to a user-defined normal-tangent axis orientation.

The relative tangential velocity components for these PIM models are controlled via user input either through an impulse ratio (Brach’s model) or a post-impact relative slip velocity value normalized by the initial relative tangential velocity component (slip ratio models). PC-Crash, a commercially available accident analysis software program that includes a PIM collision model, employs a kinetic coefficient of restitution and uses either a “full-impact” model or a “sliding-impact” model depending on the impact configuration and the user selected value of the impulse ratio (referred to as a friction parameter) [9]. For the slidingimpact model, an impulse ratio is used and the solution is identical to that of Brach’s model. For full impacts, the PC-Crash model solution is controlled by the value of the restitution coefficient and the constraint that, at the end of the compression phase, neither sliding along the tangent axis nor relative velocity parallel to the normal axis is present (Virtual Crash also utilizes a similar bounding condition in its collision model [10]). Though the PC-Crash

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model employs a kinetic coefficient of restitution, it is shown in Appendix A that, in application, it is equivalent to the kinematic definition used in the derivation of the other models. Stronge’s coefficient has not found usage in the PIM models commonly utilized in the field of accident reconstruction.

Conceptually, the PIM models described above condense the complex structural deformation and inter-vehicle interaction occurring within the contact region of automobile collision partners (left panel of Figure 2) to collision partners with rough surfaces and rigid bodies that are tangent to one another at the user-prescribed IC (right panel of Figure 2): rough surfaces because tangential forces are included in the models, and rigid bodies because the impact is considered to occur instantaneously and vehicle deformations are not included in the models. The tangent line at the IC is determined by the user-selected orientation of the normal-tangent coordinate axis.

the corresponding relative velocity components parallel to the tangent axis. The remaining parameters are constants whose values depend on impact configuration geometry, vehicle mass, and vehicle yaw inertia.

Equations (4) and (5) can be rearranged to form linear equations in impulse space. These rearranged equations are, using a kinematic restitution coefficient and a slip ratio (σ), as follows:

(6) (7)

Equations (6) and (7) are linear equations in impulse space, and the intersection of these two lines provides the solution for a given set of initial-velocity and impact-configuration inputs. Two fundamental lines in impulse space are the Maximum Compression Line and the No Slip Line.

The Maximum Compression line is found by setting the Solutions Viewed in Impulse Space coefficient of restitution to zero in equation (6), and the PIM solutions can be plotted in impulse space (i.e., nor- No Slip Line is found by setting the slip ratio to zero in mal impulse (PN) versus tangential impulse (PT)) which equation (7). The intersection of these two lines defines provides a graphical depiction of the solutions [11]. The the impulse space solution where a common velocity exists underlying basis for this plot is the similar set of equations at the end of the impulse at the IC (i.e., there is no relative that can be derived from each of the impulse-momentum velocity at the IC in either the normal or tangential direcmodels discussed here. They are, using Brach’s nomencla- tion). This common velocity solution is depicted as Point A in Figure 3. ture:

(4) (5)

Here the parameters VrN and V'rN are the pre- and postimpact relative velocity components parallel to the normal axis as calculated at the IC; the parameters VrT and V'rT are

For non-zero values of the coefficient of restitution, solutions in impulse space are defined along what is called a Restitution Line, which is parallel to the Maximum Compression line (see Figure 4). For practical values of restitution typically used in accident reconstruction analyses (i.e., greater than zero) the Restitution Line will be located above the Maximum Compression Line for the depicted quadrant. For non-zero slip ratio values, equation (7) describes a locus of solutions along a Slip Line which is par-

Figure 2: Conceptual Representation of Planar Impact Mechanics Assumptions www.collisionpublishing.com

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direction of the initial relative slip velocity) result in Slip Lines to the right of the No Slip Line. The solution for the slip ratio PIM model, with non-zero restitution and slip ratio, is then the intersection of the Restitution Line and the Slip Line and is depicted as Point B in Figure 4.

The impulse space solution for Brach’s model (also for the PC-Crash and Virtual CRASH sliding model) is simply the intersection of an Impulse Ratio Line and the Restitution Line. Since we’re plotting normal impulse versus tangential impulse, the slope of the Impulse Ratio Line is actually the inverse of the selected impulse ratio value, as expressed in equation (8). Thus, equations (6) and (8) form a pair of impulse space solution equations for impulse ratio PIM models.

Figure 3: Common-Velocity Solution in Impulse Space

Figure 4: Impulse-Momentum Solutions Along the Restitution Line in Impulse Space allel to the No Slip Line. In Figure 4, positive slip ratio values (i.e., relative sliding at separation continues in the same direction as the initial relative slip velocity) result in Slip Lines to the left of the No Slip Line, and negative values (i.e., relative sliding at separation is in the opposite 64 Collision Magazine - Volume 16 Issue 1

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(8)

The Impulse Ratio Line in Figure 5 depicts the case for what Brach calls the critical impulse ratio (i.e., no relative slip velocity at the IC at the end of the collision) [6] with the solution depicted as Point C in the figure at the intersection of the Restitution Line and the No Slip Line. Note that for this critical impulse solution the intersection of the Impulse Ratio Line and the Maximum Compression Line is to the right of the No Slip Line. This indicates that, at the end of compression along the normal axis, positive relative slip velocity is present in the tangential direction at the IC. Solutions at other locations in impulse space can readily be arrived at by changing the impulse ratio value and, thus, the slope of the Impulse Ratio Line.

In the PC-Crash and Virtual Crash collision models, the solutions are constrained to impulse ratio values equal to, or less than, a limiting value. This limiting impulse ratio value is that which produces a solution where no relative velocity exists in either the normal direction or the tangential direction at the end of compression, thus it passes through Point A. The solution is defined by a line from the origin of the impulse-space coordinate system through Point A (the common velocity condition at the end of compression) and, if a non-zero value for restitution is used, on to the ultimate solution at the intersection with the Restitution Line where the impulse solution is greater than the impulse at Point A by a factor of (1+ε). An example of what this looks like in impulse space is depicted in Figure 6 where the Restitution Line intersection occurs at Point D. The impulse ratio that defines the limiting Impulse Ratio Line indicated in Figure 6 has been demonstrated to be equivalent to what Ishikawa referred to as the Generalized Impulse Ratio (GIR) [12]. The GIR, using Brach’s nomenclature, is defined in equation (9), where the parameter r is the ratio of VrT and VrN.

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Figure 5: Impulse-Momentum Solutions Along the Friction Line in Impulse Space

(9)

In both PC-Crash and Virtual CRASH, the user can provide an impulse ratio of their choosing. However, if it exceeds the GIR value resulting in an Impulse Ratio Line to the right of the Generalized Impulse Ratio Line in the quadrant shown in Figure 6, the solution reverts to a solution along the GIR at the Restitution Line determined by the user-specified coefficient of restitution. <Figure 6 here> Note that, in Figure 6, the impulse solution at Point D lies to the right of the No Slip Line. As described in reference [12], for non zero coefficient of restitution values, the GIR bounding solution results in a post-impact relative slip velocity direction opposite that of the pre-impact relative slip velocity direction – a so-called “superball” effect. As is shown in Appendix B, at this bounding condition, the value of the resulting slip ratio is equal to the negative of the coefficient of restitution value. Thus, when using PCCrash or Virtual CRASH, impulse ratios equal to or less than the GIR and greater than the critical impulse ratio will result in reversed relative slip velocities at the IC, even though, in PC-Crash vernacular, these would be classified as sliding impacts.

Figure 6: PC-Crash Solutions in Impulse Space Normal-Tangent Axis Orientations Rose, et al. [13] conducted a PIM analysis of NHTSA crash test #4363 (involving a 1997 Chevrolet Blazer and a 1997 Honda Accord) and arrived at a solution that matched well with the post-impact velocities determined from instrumentation data recorded in that test. The PIM configuration for their analysis solution is shown in Figure 7. It can be shown that, using the same IC location, identical PIM solutions can be arrived at with a wide variety of normal-tangent axis orientations through particular combinations of the coefficient of restitution and the slip ratio or the impulse ratio. Though the space-fixed post-impact velocity-state solution and total energy loss for each of the axis orientations are the same, their solution locations in impulse space differ. Solutions for normal axis orientations ranging from 16 degrees to 75 degrees are plotted in impulse space in Figure 8. The 28 Degree solution in this figure represents the special case where the PIM normal axis orientation is aligned with the resultant impulse vector and the solution lies solely on the normal axis of the impulse-space plot. The inclusion of the 16-degree solution will become apparent later in this discussion.

Since each of the solutions depicted in Figure 8 produce the same space-fixed post-impact velocity state, the resultant impulse vectors have the same magnitude and direction relative to a space-fixed coordinate system. Thus, all of the identical solutions, at this particular IC location,

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fall on the indicated Resultant Impulse Circle (RIC). The RIC is thus a locus of solutions in impulse space that produce the same space-fixed impulse vector. Using equations (6) and (7), the restitution and slip ratio that provide a solution on the RIC for a given tangent axis orientation are defined in equations (10) using Brach’s nomenclature. The corresponding impulse ratio is, of course, simply the ratio of the target tangential and normal impulse components transformed to the specified normal-tangent coordinate system orientation.

(10)

The restitution and impulse ratio values used in the solutions of Figure 8, as well as pertinent relative velocities at the IC, are presented in Table 1. Values for a 32 Degree solution are also included in Table 1, and, like the 16 Degree solution, the inclusion of this solution will become apparent as the discussion progresses. The restitution values listed in the table (ranging from 0.076 to 0.180) are not unusual as automobile collisions go, considering that they are within the range of values observed in full-scale automobile crash testing [14]. Unlike for vehicle to-barrier or centered, collinear vehicle-to-vehicle crash tests where there is little to no yaw rotation, there is no convenient way to directly determine a restitution value with instrumentation data from a non-central, oblique crash test configuration. In light of this, the authors of reference [13] used Brach’s model and an optimization process to determine a PIM solution for the collision. The PIM solution they found (the 55 Degree solution) matched well with the crash test data and they thus referred to the restitution

value used to obtain this solution (0.126) as the “actual” restitution of the collision. This value was then used as a reference to which coefficients of restitution arrived at by other means were compared. However, given that many identical solutions can be found on the RIC, and that the range of restitution values for these solutions is not atypical in the context of automobile collisions, does an “actual” value for this collision actually exist?

Setting up a normal-tangent coordinate system orientation for oblique collisions is not necessarily a simple matter. The tangent axis is thought of by some as a plane upon which relative sliding occurs with restitution acting orthogonally to that plane [15, 16]. This does not narrow things down for us given that non-zero relative slip velocities (i.e., sliding) exist in all the normal-tangent axis orientations listed in Table 1. Brach [17] has stated, “The choice of a normal and tangential (n, t) coordinate system requires judgment of the analyst since the common surface of the vehicles changes throughout contact. In some cases, the choice can be difficult; frequently an undeformed surface can be used.” For oblique collisions, Brach et al. [18] noted that “… the angle Γ [angle to the tangent axis] must in some way account for the two independent, vehiclebased normal directions from which the crush energies have been determined,” and went on to describe the use of a tangent axis orientation that is half of the angle made between involved vehicle undeformed surfaces in their impact configuration. Germane & Gee [19] state that a slip line (i.e., tangent axis) “is often selected to coincide with the impact line, which is perpendicular to the approach velocity of the colliding bodies.”

Figure 7: Rose, et al. [13] PIM Impact Configura- Figure 8: Impulse Space PIM Solutions as a Function for NHTSA Test #4363 tion of Normal Axis Orientation 66 Collision Magazine - Volume 16 Issue 1

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Table 1: Comparison of PIM Parameters Though terms like “crush surface,” “impact surface,” “common surface,” “slip plane,” “contact plane,” “collision plane,” etc. have been used in the literature in reference to the tangent axis, there is no modelling whatsoever of distributed forces acting over “planes” or “surfaces” in the derivation of the PIM equations referred to herein. Rather, as pointed out above, the PIM derivations make use only of a single point of impulse exchange and the direction in which the restitution and slip/impulse ratio constraint equations act vis à-vis the analyst-specified normal-tangent axis orientation. In many automobile collisions the energy loss is predominantly due to plastic structural deformation as a result of impact forces; it therefore seems appropriate to associate, in some fashion, the displacement direction of the vehicle structures with the PIM normal direction in which we apply a restitution constraint.

Crush measurements included in the NHTSA #4363 crash test report are included but only for the longitudinal direction; lateral displacements were not reported. However, in looking at the post-test photographs of the #4363 crash test vehicles in Figure 9, we can see that the direction of the crush damage for the Accord is rearward and to its right, and the damage direction for the Blazer is rearward and to its left. Given these displacement directions, a potential maximum normal axis angle might be one that is aligned with the front surface of the Blazer – in this case, referring to Figure 7, a normal axis

angle of 31.6 degrees (solution parameters included in the 32 Degree line of Table 1). If we wish to establish a lowerlimit normal axis angle based on potential crush direction, the approach velocity alignment mentioned by Germane & Gee [19] may well be an option. For the #4363 crash test, this means a normal axis angle of 15.8 degrees (the 16 Degree solution line in Table 1). By way of coincidence, due to the fact that the two test vehicles are traveling at nearly the same speed at impact, the 15.8-degree normal axis angle is the same as one would get using the half-angle orientation described by Brach et al. [18].

In Figure 10, the 55 Degree, 32 Degree, and 16 Degree solution normal axis angles are depicted relative to the re-

Figure 9: Residual Crush Damage of NHTSA Test #4363 Test Vehicles: Accord (top), Blazer (bottom) www.collisionpublishing.com

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spective vehicles. Included in this figure are vectors (red), normal to the respective tangent axes, representing the direction in which the restitution constraint acts. It is clear from this figure that the 55-degree normal axis line resembles, in an approximate sense, the residual crush profiles of the test vehicles and results in a normal direction vector relative to the Accord that is rearward and rightward, similar in directionality to the structural displacement of the actual test vehicle. The normal vector relative to the Blazer, however, is directed rearward and to the right, whereas the structural displacement of the crash-tested Blazer is rearward and to its left. The normal axis angle range of 15.8 degrees to 31.6 degrees, on the other hand, better approximate the directionality of the observed test vehicle crush directions for both vehicles. Though we don’t have a detailed crush profile that includes both longitudinal and lateral displacement, it is likely the crush vectors of the test vehicles are more closely oriented with the PIM normal axes defined by this normal axis orientation range than the 55-degree normal axis. Recall from Table 1 that the 55 Degree solution utilized the critical impulse ratio and resulted in no relative slip velocity at the end of the impulse.

For the 16 Degree to 32 Degree normal axis range, there is relative slip velocity present at the IC at the end of the impulse (4.2 mph and 2.6 mph, respectively). In light of the vastly simplifying PIM assumption that reduces the complex spatial and temporal force interaction occurring

between the collision partners down to an interaction that occurs instantaneously at a single point in space, it is this author’s opinion that small post-impulse relative slip velocities at the IC should not be the cause of undue worry for an analyst. It is up to the respective analyst’s judgment, of course, to determine what constitutes a sufficiently small post-impulse relative slip velocity with which they are comfortable.

If an analyst wishes to compare partitioned normal-axis energy losses to calculated crush energies based on measured residual displacement of the collision partners, as Brach et al, discussed in reference [18], normal axes oriented in some manner with the material displacement of the involved vehicles in mind would seem to be best suited for this endeavor. However, partitioned energy loss comparisons should be undertaken with careful consideration.

As Brach et al. [18] explained, “The energy partitioning process…, is intuitive, and does not follow directly from any principle in mechanics.” Brach et al. [6] also notes that energy is not a vector that can be split out into discrete components, but as an approximation, the normal and tangential energy loss contributions can be apportioned as “normal effects” and “tangential effects.” Moreover, as mentioned above, structural deformation processes are not included in the derivation of rigid-body planar impact mechanics models, and calculating crush energy in oblique

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corner impacts is not at all a straight forward matter to begin with. With these caveats, an analyst who decided to use energy loss partitions (via equations (11) and (12) below from Brach et al. [18]) to refine their selection of a normal-tangent axis on our current RIC would be working with the partitioned energy loss versus normal axis orientation variations shown in Figure 11. Of note in this figure is that the 15.8 degree orientation results in a negative tangential energy loss (i.e., a work-added contribution) and a normal energy loss that is greater than the total energy loss.

This may reasonably lead an analyst to revise their range of acceptable axis orientations to include a maximum of 27.8 degrees (28 Degree solution line in Table 1) where the normal energy loss is equal to the total energy loss.

(11) (12) An interesting aside related to the 28 Degree solution is that, since the normal axis is aligned with the PDOF in this PIM configuration, by definition there is no impulse acting along the tangential axis (i.e., µ = 0) which leads to the following equations relating the pre- and post-impulse velocities at the CG oriented along the tangential axis:

(13)

Using rigid-body relationships to rewrite these equations in terms of velocities at the IC and angular velocities, we get the following equation for the change in post-impulse relative slip velocity at the IC:

(14)

Thus, despite there being no impulse acting in the tangential direction in the 28 Degree solution, the relative slip velocity fell from an initial value of 14.1 mph to a final value of 3.0 mph. In looking at equation (14) we see that this relative slip velocity difference is solely a result of the selected IC location and the change in yaw rates of the respective vehicles induced by the normal impulse. This fact has ramifications in CRASH-type analyses as well. It is a straightforward, though algebraically laborious, exercise to show that when the impulse ratio is set to zero in the PIM equations, they can be reduced identically to those for delta-V in the CRASH-type methodology. Therefore, slip velocity changes at the point of impact (i.e., the IC) in CRASH-type analyses are out of the direct control of the analyst, and claims of a common velocity condition at the point of impact are valid only for the direction parallel to the PDOF when the coefficient of restitution is set to zero.

Figure 11: Energy Loss Partitions versus Normal Axis Orientation Conclusion In drawing this article to a close, we have seen that, for a given solution impulse vector, the restitution and tangential constraint value combinations, as well as the partitioned energy values, are regulated by the orientation of the normal-tangent coordinate axes. We have also seen that, once an acceptable impulse vector solution has been found by an analyst, an RIC can be created in impulse space that provides the same solution impulse vector with respect to a space-fixed coordinate system, as well as the respective vehicle-relative coordinate systems for a range of normal-tangent coordinate axis orientations. Thus, the impulse vector, all velocity vectors, and the total energy loss will be the same regardless of the selected normal-tangent axis orientation on the RIC. Though any normal-tangent orientation on the RIC will provide the same ultimate result, as automobile accident analysts we place automobile collisions in context, particularly with respect to the coefficient of restitution parameter and its association with energy loss, and search for solutions with constraint parameter values, and perhaps energy partition values, that make sense to us based on our education, training, and experience. Not surprisingly, as it is in many situations encountered in the field of automobile accident reconstruction, the selection of a PIM normal-tangent axis orientation requires engineering judgment, which, as Hauer [20] observes, “is a necessary response … to knowledge that is not perfect.”

And, speaking of knowledge that is not perfect, we have not yet begun to discuss the vagaries of impulse center location selection. Nor will we here. Perhaps an intrepid analyst out there will decide to grab a bat and take a swing at that topic. As for me, I’m heading back to the dugout.

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References 1. Newton, Isaac, “The Mathematical Principles of Natural Philosophy,” 3rd Edition, 1726, translated by Ian Bruce, 17centurymaths.com/contents/newtoncontents.html 2. Goldsmith, Werner, “Impact: The Theory and Physical Behavior of Colliding Solids,” Edward Arnold Publishers, Ltd., London, 1960.

3. Chatterjee, Anindya, “Rigid Body Collisions: Some General Considerations, New Collision Laws, and Some Experimental Data,” PhD Thesis, Cornell University, Jan. 1997. ruina.tam.cornell.edu/research/topics/collision_mechanics/

4. Robinson, Edward L., “Derivation of Closing Speed as a Function of Dissipated Energy,” Society of Automotive Engineers, Paper No. 2000-01-1318, 2000.

5. Engineering Dynamics Corporation Technical Newsletter, Spring 2007, www.edccorp.com

6. Brach, Raymond M., and Brach, R. Matthew, “Vehicle Accident Analysis and Reconstruction Methods,” Society of Automotive Engineers, Warrendale, PA, 2005.

7. Ishikawa, Hirotoshi, “Impact Center and Restitution Coefficients for Accident Reconstruction,” Society of Automotive Engineers, Paper No. 940564, 1994.

8. Smith, Gregory C., “Conservation of Momentum Analysis of Two-Dimensional Colliding Bodies, With or Without Trailers,” Society of Automotive Engineers, Paper No. 940556, 1994.

9. Steffan, Hermann, & Moser, Andreas, “The Collision and Trajectory Models of PC-CRASH,” Society of Automotive Engineers, Paper No. 960886, 1996.

10. Virtual CRASH, LLC, User’s Guide (online edition) Appendix 1: Single Body Collision Physics Model, www.vcrashusa.com/guide.

11. Routh, Edward J., “An Elementary Treatise on the Dynamics of a System of Rigid Bodies,” Third Edition, Macmillan and Co., London, pp. 131-146, 1887.

12. Marine, Micky C., “On the Concept of Inter-Vehicle Friction and its Application in Automobile Accident Reconstruction,” Society of Automotive Engineers, Paper No. 2007-01-0744, 2007.

13. Rose, Nathan A., Fenton, Stephen J., and Beauchamp, Gray, “Restitution Modeling for Crush Analysis: Theory and Validation,” Society of Automotive Engineers, Paper No. 2006-01-0908, 2006.

14. Monson, Kenneth L., and Germane, Geoff J., “Determination and Mechanisms of Motor Vehicle Structur70 Collision Magazine - Volume 16 Issue 1

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al Restitution from Crash Test Data,” Society of Automotive Engineers, Paper No. 1999-01-0097, 1999.

15. Kolk, H., Tomasch, E., Sinz, W., Bakker, J., and Dobberstein, J., “Evaluation of a Momentum Based Impact Model and Application in an Effectivity Study Considering Junction Accidents,” 7th International Conference, Expert Symposium on Accident Research, 2017.

16. Carpenter, Nicholas, and Welcher, Judson, “Inter-Vehicular Sliding Friction and Crush Energy Losses in Impulse Momentum Planar Collision,” Society of Automotive Engineers, Paper No. 2019-01-0422, 2019.

17. Brach, Raymond M., “Energy Loss in Vehicle Collisions,” Society of Automotive Engineers, Paper No. 871993, 1987.

18. Brach, Raymond M., Welsh Kevin J., and Brach, R. Matthew, “Residual Crush Energy Partitioning, Normal and Tangential Energy Losses,” Society of Automotive Engineers, Paper No. 2007-01-0737, 2007.

19. Germane, Geoff J., and Gee, R. Shane, “Introduction of Pulse Shapes and Durations into Impulse-Momentum Collision Models,” Society of Automotive Engineers, Paper No. 2005-01-1183, 2005.

20. Hauer, Ezra, “Engineering Judgment and Road Safety,” Accident Analysis and Prevention 129, pp. 180189, 2019.

Appendix A: Kinematic and Kinetic PIM Restitution Equivalence

The use of a kinetic coefficient of restitution results in the following (where PNc and PTc are the normal and tangential impulses at maximum compression):

(A1) (A2)

At maximum compression, the impulse ratio is therefore:

(A3)

Using equation (4) from the main text above, the normal impulse at maximum compression is then:

(A4)

Utilizing equation (A1), equation (4) can be rewritten as follows:

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The PC-Crash full impact condition is zero slip at the end of compression, therefore from equation (B1) we get:

(A5) Substituting equation (A4) into equation (A5) and rearranging, we get:

(A6)

Thus, the kinetic definition used in PC-Crash is equivalent to the kinematic definition where VrN and V’rN are the preand post-impact relative velocities normal to the tangent axis.

Appendix B: PC-Crash Full Impact and Virtual CRASH Bounded Solution Slip Ratio Starting with equation (5) from the main text above:

C ollision

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Investigation of EDR Data

From a High Spped Crash with 3D Simulation

(B1)

(B2)

Utilizing equation (A2), equation (B1) can be rewritten as follows:

(B3) Substituting equation (B2) into equation (B3) and rearranging, we get the slip ratio for the PC-Crash full impact condition:

(B4)

Thus, the slip ratio result in a PC-Crash full impact (and for the Virtual CRASH bounded solution) is equal to the negative of the selected coefficient of restitution.

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Analytical Method foR Correcting the Delta-V Reported by Toyota/Lexus/Scion

Airbag Control Modules

Robert Anderson

Biomechanics Analysis

I

Michelle Hoffman

Forensic Injury Analysis

ntroduction In mid-2011, the Toyota family (Toyota, Lexus and Scion) of vehicles became Bosch Crash Data Retrieval (CDR) Tool supported with the release of Version 4.0 of the Bosch CDR Tool software and by the end of 2011, coverage had been extended as far back as the 2001 model year with CDR Tool Version 4.3.[1] Barrier crash testing of various Toyota vehicles began in late 2012 and the growing body of results were presented at the 2013 CDR User’s Summit, the 2013 SATAI Spring Conference, and the 2013 ARC-CSI Crash Conference.

Consistent with testing conducted by other researchers, it was observed that an impact producing an acceleration with a magnitude of approximately 2 gs was required to wake the Toyota Airbag Control Modules (ACMs) and record an event. For Toyotas, like most other vehicles that are equipped with Event Data Recorders (EDRs) that have a similar wake up, AE, algorithm "wake up" or trigger threshold, there is a potential to under-report the magnitude of the delta-V due to not capturing and then not recording the portion of the delta-V that occurs before "wake up" or the "Time Zero" point.

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W. R. Rusty Haight

Collision Safety Institute

positive X-directed (rear-end) impacts, and under-reported in negative X-directed (frontal) impacts.[2,3] It is generally accepted that the discrepancy in CDR reported delta-V is the result of the ACM’s internal accelerometer not being zeroed, which produces an offset, or bias, in the accelerometer data. Consequently, even at rest, integrating the non-zero accelerometer signal will yield an everincreasing or ever-decreasing delta-V. In effect, the CDR Tool reported delta-V can be thought of as the delta-V from the impact plus or minus the accumulated speed change from the accelerometer offset.

In addition, by comparing the delta-V measured in crash tests to the CDR Tool reported delta-V, it soon became evident that, particularly in lowspeed impacts, the CDR Tool reported delta-V from Toyota GEN1 ACMs and 04EDR/GEN2 Camry and Yaris ACMs was over-reported in

To estimate the actual delta-V from that recorded by the ACM, the practice of adjusting the CDR Tool reported delta-V by an average or range of average errors has become common.

Another method for estimating the actual vehicle delta-V from that reported by Toyota ACMs exhibiting accelerometer bias involves correcting the shape of the delta-V trace.[2] This analytical method is specified in SAE J211 as a requirement to correct data from non-zeroed accelerometers in crash tests.[4] The accelerometer data is corrected by shifting the acceleration data up or down until the integration trace of that acceleration produces the characteristic wave shape which flattens out or plateaus as the crash pulse ends. By way of demonstration, Figure 1 is an example of a set of corrected and uncorrected data.

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Comparing the CDR Tool reported parameters in barrier crashes to data in the same crashes collected with calibrated reference instrumentation installed in the crash-tested vehicles, an understanding of some system behaviors and relevant parameters can be gained, such as recording order,[5] the ACM wake threshold, and the ACM accelerometer offset. It also gives an opportunity to evaluate the performance of different delta-V correction methods. This paper presents the results of the specified analytical method required in SAE J211 to correct data from non-zeroed accelerometers for a series of barrier impacts and car-to-car crash tests involving Toyotas.

Literature Review Prior to Toyota systems being accessible using the Bosch CDR Tool, when a Toyota "EDR Tool Operator" (technician) would access and retrieve data from a Toyota system using the Toyota Read Out Tool (ROT) they would distribute, with the retrieved data report, a document bearing the title "Event Data Recorder – Reference Document"[6].

Toyota long held that the ROT was variously a "proprietary, in-house, or prototype tool" before the Toyota systems became accessible using the Bosch CDR Tool. As part of that original documentation when addressing EDR data accuracy, Toyota offered: "The accuracy of the data from the EDR depends on the collision and the EDR ca-

pabilities. Government studies of Toyota EDRs indicate that Toyotas EDRs have similar capabilities to other vehicle manufacturers" however no documentation associated with the "government studies" is found as part of that document. The ROT documentation also addressed, generally, the recording trigger threshold. Notably, the statement reflects the accuracy of the data, not separately the functionality of the ROT tool.

Comeau et al., reported the results of 25 to 35 mph frontto-barrier crashes. The pre-crash speeds reported by the ROT were within approximately 1.25 mph of the reference instrumentation, and the ROT reported delta-Vs were under-reported by approximately 4% in 12 of the 14 test vehicles.[7] For the remaining 2 test vehicles, which were in 35 mph barrier crashes, anomalous results were obtained in which the ROT under-reported the delta-V by 12 to 14 percent.

Exponent subjected 7 test vehicles to deployment barrier crash tests where the impact speeds ranged from 17 to 50 mph and obtained EDR reports using the Toyota ROT.[8] The EDR reported delta-V was generally accurate within 5 percent of the reference delta-V for barrier crashes up to 40 mph. In the 50-mph barrier crash, the ACM detached from the vehicle and under-reported that actual delta-V by 20 mph.

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In 2012, Rick Ruth summarized another eight studies that pre-dated the release of CDR Tool Version 4.0, and concluded that the Toyota EDR reported delta-V and precrash speed data was just as accurate as data from EDRs found in GM, Ford and Chrysler vehicles, which had been utilized by safety researchers, law enforcement and crash reconstructionists over the preceding nearly 10 years.[9] It is worth noting that to compare the delta-V obtained from the Toyota ROT as indicated in the "Event Data Recorder – Reference Document"[6] with data from testing instrumentation, the polarity of the ROT reported delta-V was changed since that polarity was reported opposite to the polarity specified by SAE J211. In the Toyota "Event Data Recorder – Reference Document" one finds this passage with respect to the displayed velocity change data table and graph: "Post-Crash Data – (Note) 22. Vel Chg- this shows the longitudinal velocity (speed) change of the vehicle from the trigger event. The data is positive for deceleration (such as a frontal crash) and negative for acceleration (such as a rear impact). This data is taken where the airbag center sensor assembly ECU is located."

For the remainder of the studies summarized here, the EDR report was obtained using the Bosch CDR Tool, which observes SAE J211 polarity.

At the 2013 CDR User’s Summit, the then-current progress of the subject barrier crash test results was presented. At that time, the crash program included two Toyota GEN1 (02EDR) vehicles, two GEN2 (04EDR) vehicles and one GEN2 (06EDR) vehicle. The low-speed deltaV anomaly from non-zeroed ACM accelerometers in the GEN1 vehicles and 04EDR Camry and Yaris outlined above was noted at that time and the proposition that the SAE J211 method to obtain the correct delta-V by effectively re-zeroing the acceleration data was set forth.[2] MEA Forensics published the results of 71 vehicle-to-barrier crash tests with 5 extra ACMs mounted on the right front floor of the tested 2005 Toyota Corolla with delta-Vs up to 6¼ mph. The same 6 ACMs were then subjected to a series of crash pulses on a linear sled. It was found that the ACM reported delta-V in frontal collisions was under-reported by 0.8 to 1.6 mph, and the delta-V from rear-end collisions was over-reported by 0.4 to 1.4 mph.

The threshold acceleration for triggering a recording was found to be about 2 gs. The average accelerometer bias evidenced by the slope of the delta-V after the crash pulse was complete was 0.4 gs. The delta-V error increased with increased duration and decreased peak acceleration. In their

test series, a frontal non-deployment event was never overwritten by a subsequent rear-end event.[3] In a follow-up study, GEN1, GEN2 and GEN3 Toyota EDRs were subjected to linear sled tests and it was again observed that the GEN1 ACMs, and a Camry ACM with a GEN2 04EDR under-reported frontal delta-Vs and over-reported rear-end delta-Vs.[10] Ruth & Muir reported on front and rear car-to-car impacts with ride-along ACMs that produced 2.5 to 3.7 mph delta-Vs. The results indicated that there was an average accelerometer bias of 0.87 gs for the 2007 Yaris, which is equipped with a GEN2 04EDR. The different accelerometer bias than that observed by Wilkinson, et al. raised the question if the amount of accelerometer bias depended on the Toyota EDR or vehicle model.[11] MEA Forensics published regression models for Toyota GEN1, GEN2 and GEN3 ACMs based upon barrier and car-to-car crashes with delta-Vs up to 7.5 mph, as well as sled test results with delta-Vs up to 10.5 mph. The simple regression model for use in crash reconstruction accounted for 96 percent of the variation in CDR reported delta-Vs. The three ACM generations performed similarly in frontal impacts. The CDR reported delta-V was under-reported in frontal impacts, but was within 0.9 mph of the test measured delta-V. However, different rear-end impact responses were observed between vehicle models and EDR generations. In rear-end impacts, the reported delta-V was over-reported, but fell within 1.5 mph of the measured delta-V.[12] In 2012, the National Highway Traffic Safety Administration (NHTSA) published and made effective an EDR regulation as part of the Code of Federal Regulations (CFR): 49CFR563 "Event Data Recorders." The regulation applies to passenger cars, light trucks and SUVs made on or after September 1, 2012 and in which the auto manufacturer elected to install a device or function which meets the definition in the regulation (49CFR563.5) of an "Event Data Recorder." In that regulation, we find definitions (49CFR563.5), Required Data Elements (Table I at 49CFR563.7), conditionally required data elements (Table II at 49CFR563.7) and the required Data Format for data elements (Table III at 49CFR563.8).

Before Xing, et al., in 2016, all of the papers referenced above explored data related to vehicles built prior to the regulatory compliance start date of September 1, 2012 ("pre-563 vehicles"). It bears observing that the regulation calls for (Table III at 49CFR563.8) a specified level of accuracy for longitudinal and lateral delta-V of +/- 10% on a full range of -100 to +100 km/h over a period of 250 to

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300 ms depending on the specific element (subject to an indication of a point where the data exceeded the range of a sensor).

Materials and Methods Test Vehicles

In 49CFR563, time zero (T0) is defined as whichever occurs first: the time at which the occupant restraint control algorithm is activated for “wake-up” systems, the first point where a longitudinal delta-V of over 0.5 mph is reached within a 5 ms time period for continuous running algorithms, or a deployment is commanded.

Soon after Toyota became Bosch CDR supported, the authors began conducting instrumented crash tests to evaluate the CDR reported delta-V compared to the delta-V from reference instrumentation. The vehicles in this test series are listed in Table 1.

In SAE J1698 (rev 5/2014), "time zero" is referred to as "The beginning of a crash event." In SAE J1698-1[13] the definition of "Beginning of Impact Event (Time Zero)" mirrors that found in 49CFR563 but adds this caveat: "The beginning of an Impact Event (defined herein) shall not be interpreted as the moment when the subject vehicle makes a first physical contact with another object. The beginning of an event also does not mark the condition that determines whether to record the event data associated with the event for subsequent retrieval. The purpose of defining the beginning of an event is to enable the alignment of data elements from multiple recording devices on a vehicle."

A series of 44 barrier crash tests were conducted with Toyota vehicles equipped with GEN1, GEN2 and GEN3 EDRs. Each vehicle was propelled forward or backward into a concrete barrier (Figure 2) by manually pushing the vehicle with engine running and the transmission in neutral while being steered by a human occupant. The pre-impact speeds changed slowly with an average acceleration of about 0.04 gs before leveling out near the intended impact speed, which was generally within the 1 to 5 mph range.

Crash Tests

In addition to the barrier crashes, there were an additional 6 rear-end impacts in which a Camry was manually propelled into the rear of a Sequoia at speeds generally within the 1 to 6 mph range. Due to the difference in bumper height, these car-to-car tests were essentially bumper-tohitch receiver impacts. The vehicles were in neutral with engine running and transmission in neutral, and both were occupied by human occupants.

In keeping with the concept that crash exposures of live humans can generally be safely conducted with delta-Vs up to about 11 mph in rear-end impacts and up to 20 mph or higher in frontal impacts, [14,15,16,17] the testing was planned and executed to produce delta-Vs with magnitudes less than 8 mph.

Table 1: The model year and EDR generation of the test vehicles.

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Figure 2: The concrete crash test barrier

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Instrumentation Each vehicle was instrumented with a 100 g triaxial accelerometer mounted at the vehicle’s approximate static center of gravity (cg) on the vehicle chassis and/or on the Toyota's ACM itself. The data was collected at 10,000 Hz using a Diversified Technical Systems TDAS Pro data acquisition system and filtered in accordance with SAE Surface Vehicle Recommended Practice J211-1.[4] The TDAS is a 16-bit data acquisition system, meaning that each parameter's resolution is the measurable range divided by 216 or 65,536. For the 100 g accelerometer, the resolution is 0.003 gs. A pressure sensitive tape switch was mounted to the bumper of each tested vehicle that signaled time zero.

Delta-V was defined as the integral of vehicle's X-axis acceleration from tape switch trigger until the acceleration returned to zero.

In the Yaris test series, vehicle acceleration was also measured using an IST EDR-3, which is a 10-bit data acquisition system with an internal triaxial 50 g accelerometer.

The IST was set to collect data at 3200 Hz and data collection was triggered by the level of acceleration. Time zero was defined as when the acceleration departed from zero and the delta-V was defined as the integral of the vehicle's X-axis acceleration from time zero until that acceleration returned to zero.

Vehicle speed was recorded using a Racelogic VBOX III. The VBOX III collects data at 100 Hz, with speed derived from the Doppler shift of GPS radio signals reported to be

accurate to 0.06 mph. Vehicle speed was also measured in some tests using a FarmTek time trap that consisted of two light beams and sensor pairs, or two pressure sensitive tape switches, spaced one foot apart. The time trap has a 1 ms resolution, so that with a 1 foot spacing, the resolution is 0.08 mph at 5 mph.

Before each test series, a baseline CDR data file was obtained using the Bosch CDR Tool, and then a CDR data file was obtained again after each test.

Data Processing For each test that resulted in a CDR event, the ACM’s delta-V was recorded. The delta-V used for analysis was either the maximum absolute value, or the maximum absolute delta-V value immediately before the upward deflection in the delta-V, which is an indication of a non-zeroed ACM accelerometer. Examples of the selected delta-V value from the ACM are shown in Figures 3 and 4.

When accelerometer bias was evident, the delta-V plot from the ACM was differentiated to get an acceleration trace, which was shifted until re-integration of the plot resulted in a delta-V trace that on average, reached a plateau.

The amount of shift (measured in gs) necessary to reach this plateau was recorded. In addition, by comparing the reference graphs to the ACM graphs, the amount of timeshift between the reference instrumentation and the ACM accelerometer could be visualized.

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Figure 4: The value of delta-V used from a frontal impact test exhibiting accelerometer bias The ACM delta-Vs were also adjusted using the regression models set forth by MEA Forensics. When there was not a regression model specific for the test vehicle, the average of the regression models for the EDR generation was used.

The correction by re-zeroing the acceleration or the adjustments made by regression model to the ACM deltaVs were judged by comparing the results to the delta-Vs obtained by integrating the acceleration from the reference instrumentation.

For the 2013 Toyota Corolla, which was equipped with a GEN3 EDR, the manner in which the T0 was established and the ACM delta-V was recorded was investigated by comparing the ACM recorded delta-V with both the reference delta-V and the reference delta-V after the reference acceleration reached a magnitude of 2 gs.

Results GEN1 Vehicles

rected, the ACM delta-V over-reported rear-end impacts and under-reported frontal impacts by an average of 0.56 mph. An average shift of -0.3 gs (range of -0.2 to -0.45 gs) was necessary to re-zero the derived accelerometer data in order to produce delta-V graphs that plateaued. The raw ACM delta-V, the delta-V from re-zeroing and regression adjusted delta-Vs versus the reference delta-V are shown in Figure 5.

For the 2002 Camry, correcting the delta-V by re-zeroing the ACM acceleration resulted in a difference with the reference delta-V that was on average 0.15 mph and adjusting the delta-V using the regression model developed by Lee et al., resulted in an average error of 0.4 mph.

The 2005 Corolla was equipped with an 02EDR. An event was recorded in all 7 of the Corolla’s barrier tests, but the reference accelerometer data was lost for one of the frontal impacts.

Uncorrected, the ACM delta-V over-reported rear-end imThe EDR data files from the GEN1 vehicles, 2002 Camry, pacts and under-reported frontal impacts by an average of 2005 Corolla and 2005 Sequoia, did not contain longitu- 0.87 mph. An average shift of -0.3 gs, ranging from -0.1 to dinal acceleration but did include recorded delta-V. The -0.7 gs, was necessary to re-zero the derived accelerometer delta-V data table and accompanying graph began at 10 data in order to produce delta-V graphs that plateaued.

The raw ACM delta-V, the delta-V from re-zeroing and ms with a non-zero value and went to 150 ms. regression adjusted delta-Vs versus the reference delta-V The 2002 Toyota Camry was equipped with an 00EDR. In are shown in Figure 6. the car-to-car rear-end or hitch receiver impacts, an event was recorded in the Camry in 5 of the 6 tests. Uncor- For the 2005 Corolla, correcting the delta-V by re-zeroing the ACM acceleration resulted in a difference with the 78 Collision Magazine - Volume 16 Issue 1

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reference delta-V that was, on average, 0.04 mph and adjusting the delta-V using the regression model developed by Lee et al., resulted in an average error of 0.09 mph.

Figure 5: Raw ACM, re-zeroed and regression delta-Vs versus reference delta-V for the 2002 Camry

The 2005 Sequoia was equipped with an 02EDR. The Sequoia was subjected to 7 barrier impacts that produced 6 recorded events. The Sequoia was also subjected to 6 car-tohitch receiver impacts that resulted in 2 recorded events. Uncorrected, the ACM delta-V over-reported rear-end impacts and under-reported frontal impacts by an average of 0.83 mph. An average shift of -0.21 gs, with a range from 0 to -0.35gs, was necessary to re-zero the derived accelerometer data in order to produce delta-V graphs that plateaued.

The raw ACM delta-V, the delta-V from re-zeroing and regression adjusted delta-Vs versus the reference delta-V are shown in Figure 7.

For the 2005 Sequoia, correcting the delta-V by re-zeroing the ACM acceleration resulted in a difference with the reference delta-V that was on average 0.01 mph and adjusting the delta-V using the regression model developed by Lee, et al., resulted in an average error of 0.18 mph.

GEN2 Vehicles

Figure 6: Raw ACM, re-zeroed and regression delta-Vs versus reference delta-V for the 2005 Corolla www.collisionpublishing.com

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The EDR data from the GEN2 vehicles, 2007 Yaris, 2010 Camry and 2010 Prius, did not include longitudinal acceleration but did provide recorded delta-V. The delta-V graph began at 10 ms with a non-zero value and went to 200 ms. For the 04EDR vehicles, the longer recording tended to demonstrate the ACM accelerometer bias, as shown in Figure 3 and 4. The Prius, which is an 06EDR, had delta-V graphs that rose or fell until 80 to 90 ms and then flatlined in every case.

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The 2007 Yaris was equipped with an 04EDR. The Yaris was subjected to 10 barrier impacts that produced 8 recorded events. Uncorrected, the ACM delta-V over-reported rearend impacts and under-reported frontal impacts by an average of 1.89 mph. An average shift of -0.86 gs, with a range from -0.4 to -1.25gs, was necessary to re-zero the derived accelerometer data in order to produce delta-V graphs that plateaued.

The raw ACM delta-V, the delta-V from re-zeroing and regression adjusted delta-Vs versus the reference delta-V are shown in Figure 8.

Figure 7: Raw ACM, re-zeroed and regression delta-Vs versus reference delta-V for the 2005 Sequoia

For the 2007 Yaris, correcting the delta-V by re-zeroing the ACM acceleration resulted in a difference with the reference delta-V that was on average 0.11 mph and adjusting the delta-V using the regression model developed by Lee, et al., resulted in an average error of 0.75 mph.

The 2010 Camry was equipped with an 04EDR. The Camry was subjected to 9 barrier impacts that produced 7 recorded events. Uncorrected, the ACM delta-V over-reported rear-end impacts and under-reported frontal impacts by an average of 0.94 mph. An average shift of -0.17 gs, ranging from 0 to -0.3gs, was necessary to re-zero the derived accelerometer data in order to produce delta-V graphs that plateaued. The raw ACM delta-V, the delta-V from re-zeroing and regression adjusted delta-Vs versus the reference delta-V are shown in Figure 9.

Figure 8: Raw ACM, re-zeroed and regression delta-Vs versus reference delta-V for the 2007 Yaris

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For the 2010 Camry, correcting the delta-V by re-zeroing the ACM acceleration resulted in a difference with the reference delta-V that was on average 0.75 mph and adjusting the delta-V using the regression model developed by Lee et al., resulted in an average error of 0.65 mph.

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The 2010 Prius was equipped with an 06EDR. The Prius was subjected to 6 barrier impacts that produced 6 CDR recordings. Because the delta-V graphs plateaued or flatlined, there was not an indicator of accelerometer bias or by how much the derived accelerometer data should be shifted to be re-zeroed.

Uncorrected, the 2010 Prius ACM delta-V under-reported the magnitude of the rear-end impact delta-Vs by an average of 1.4 mph, and under-reported the magnitude of the frontal impact delta-Vs by an average of 1 mph. Comparison between the reference acceleration and the ACM derived acceleration revealed that this discrepancy was due to the ACM missing the first part of the acceleration pulse (the first 70-75 ms for frontal impacts and the first 40 to 50 ms for rear impacts). The raw ACM delta-V and the regression adjusted delta-Vs versus the reference delta-V are shown in Figure 10.

Figure 9: Raw ACM, re-zeroed and regression delta-Vs versus reference delta-V for the 2010 Camry

For the 2010 Prius, adjusting the delta-V using the regression model developed by Lee, et al., reduced the average error by about half, so that the magnitude of rear-end delta-Vs were under-reported by 0.7 mph, and the magnitude of the frontal delta-Vs were under-reported by an average of 0.46 mph.

GEN3 Vehicles The tested 2013 Corolla ACM featured a GEN3 12EDR subcomponent. EDR data retrieved from a 2013 Corolla does not report longitudinal acceleration but does record longitudinal delta-V. The tested Corolla with the GEN3 12EDR was subjected to a total of 5 barrier impacts. The first 4 impacts were front-to-barrier that only produced two recorded events. The final barrier impact was a rear-to-barrier.

Because all the recorded maximum

Figure 10: Raw ACM and regression delta-Vs versus reference delta-V for the 2010 Prius

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bias, or accelerometer data that is not zeroed. This issue has generally been observed in GEN1 (00 & 02EDR) vehicles but has also been observed in crash testing of some GEN2 vehicles; namely the Camry and Yaris equipped with 04EDRs. In EDR data obtained as a function of case work, additional models such as the Rav4 and the Lexus IS with 04EDRs have also exhibited delta-Vs characteristic of non-zeroed accelerometer data.

Figure 11: Raw ACM and regression delta-Vs versus reference delta-V for the 2013 Corolla longitudinal delta-Vs in these tests were found at under 100ms, in the data translation reports, the data tables and graphs were truncated at 100 ms and there was not a clear separate indicator of accelerometer bias or by how much the derived accelerometer data should be shifted to be re-zeroed as previously described.

For the 2013 Corolla, adjusting the delta-V using the regression model developed by Lee, et al., reduced the magnitude of the average error by 1/20th of 1 mph to 0.35 mph on average as seen in Figure 11.

Discussion Toyota was the fourth manufacturer to become Bosch CDR Tool supported.

[1] Adding the Toyota family of vehicles represented a significant increase in the number of vehicles with accessible EDR data. Toyota vehicles do not erase non-deployment events after approximately 250 ignition cycles or approximately 5 to 7 weeks of normal driving [18,19] as the majority of GM vehicles did through about MY07-10. The Toyota family of vehicles also did not suffer power depletion during recording issues or RDS reliability issues with the frequency seen in Ford systems or only record deployment events, like many Chrysler vehicles did at that time (through about MY '10). It is perhaps for this reason that in these authors’ experience, just over half of all EDR reports obtained in case work are from Toyota vehicles.

However, an issue unique to Toyota vehicles was immediately observed in lowspeed crash testing. The delta-Vs were over-reported in rear-end impacts and under-reported in frontal impacts, which is characteristic of accelerometer 82 Collision Magazine - Volume 16 Issue 1

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Comparing the acceleration derived from the CDR Tool reported deltaV to the reference instrumentation revealed that offset from the ACM’s internal accelerometer of the same vehicle varied between tests. This result is consistent with accelerometer thermal drift. In fact, accelerometers are notorious for readings that drift with changes in temperature, which is why NHTSA crash testing requires that test facilities have a temperaturecontrolled building to prepare and hold the test vehicle until immediately before the crash test and dummies or ATDs must be temperature soaked for 16 hours before testing.

[20] Accelerometer drift may explain the different offsets observed by different researchers.

Instruments such as the TDAS Pro are typically set up to avoid non-zeroed accelerometer data by automatically shifting the acceleration data so that the accelerometer reading just before T0 is zero. However, biased or non-zeroed data can still be obtained if the vehicle is hard braking (nonzero acceleration) into an impact or if there is a late trigger so that the zero reading is taken after the crash had already begun, for example. When non-zeroed accelerometer data is obtained, SAE J211 requires that acceleration data be zeroed. Indeed, the correction method in this paper is based upon this long-standing SAE recommended practice.

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The correction by re-zeroing the acceleration or the adjustments made by regression model to the ACM deltaVs were judged by comparing the results to the delta-Vs obtained by integrating the acceleration from the reference instrumentation. The uncorrected ACM delta-V, the corrected or re-zeroed ACM delta-V, and the regression adjusted ACM delta-V were plotted against the reference delta-V, shown in Figures 5 through 11. In these graphs, the data from a perfect 1-to-1 relationship between ACM and reference delta-Vs would fall on a 45° line. The distance the data falls from the 45° line represents the difference between the ACM, corrected or adjusted delta-V from the reference delta-V, and the performance of the correction or adjustment method can be visualized by the reduction in distance from the 45° line.

As outlined in the results section, although the Toyota models in this study did not report the acceleration data, re-zeroing the acceleration obtained by taking the derivative of the delta-V, proved to be an effective technique for correcting a non-plateaued delta-V graph and typically outperformed the regression model set forth by Lee, et al.[12] Unless locked ("frozen") by a previous deployment, Toyota GEN1 and GEN2 records every event that "wakes up" or "triggers" the start of the ACM deployment decisionmaking algorithm at the ACM (the 2 g level). In this regard, "triggering" the start of that algorithm also met the "trigger threshold" for recording. That recording threshold changed with later generation Toyota systems where an 8km/h (5mph) recording threshold was introduced. Toyota uses the word/phrase "trigger" and "trigger threshold" in the context of both the start of the deployment decision algorithm and the point where an event qualifies for recording; both are "triggered" points.

Consistent with testing conducted by other researchers, it was observed that an impact producing an acceleration with a magnitude of approximately 2 gs was required to wake the Toyota ACMs and record an event, as illustrated in Figure 12. For Toyotas, like most other vehicles that are equipped with EDRs that have a similar wake up, AE, algorithm "wake up" or trigger threshold, there is a potential to under-report the magnitude of the delta-V due to not capturing and then not recording the portion of the delta-V that occurs before "wake up" or the "Time Zero" point. The re-zeroing method presented here does not address that potential underreporting of the portion of the total delta-V that may have occurred before "wake up."

However, adopting a record threshold of approximately 5 mph increases the accuracy by minimizing the portion of the delta-V that occurs before 2g.

In 2002 and then in 2005, Lawrence, et al.,[21] and Wilkinson, et al.,[22] addressed the same observed underreporting in EDR delta-V data for the same reason (that being the initial portion of the acceleration occurring before "algorithm enable" was not included in the recorded delta-V) as a function of research involving late 1990's and then 2003 and 2004 vintage General Motors vehicles and ACMs, respectively. The observation is clearly not something limited to or associated with one auto manufacturer or another.

The regression method effectively accounts for the variation due to the combination of accelerometer bias and the missed delta-V before "wake-up." This provides an explanation for why the regression method outperformed re-zeroing in very low-speed impacts, such as the lowest magnitude delta-V in Figure 5, where the majority of the discrepancy with the reference value was due to the missed delta-V before "wake up" and not the non-zeroed accelerometer.

Comparison between the reference acceleration and the ACM-derived acceleration for the 2013 Corolla revealed that this apparent discrepancy was due to the ACM missing the first part of the acceleration pulse (the first 40 ms for frontal impacts and the first 30 ms for the rear impact), which is about half the missing acceleration observed in the 2010 Prius. The raw ACM delta-V and the regression adjusted delta-Vs versus the reference delta-V are shown in Figure 11.

Unlike the regression technique, which is specific to 3 Toyota models, the accelerometer re-zeroing technique is generally applicable to any vehicle’s acceleration data that is not zeroed. However, because acceleration data is not reported in Toyota data translation reports, the re-zeroing technique can only be applied to vehicles whose delta-V graph exhibits bias by not plateauing.

Because the 06EDR Prius’ delta-Vs flatlined after 80 or 90 msec, and the tested 12EDR Corolla only reported data to 100 msec, accelerometer bias cannot be corrected using the re-zeroing technique. The 06EDR and 12EDR vehicles in this study did not evidence a non-zeroed accelerometer, and the magnitude of the delta-V was somewhat underreported in both rear-end and frontal impacts, which is typical of wake-up type EDRs in low-speed impacts. In essence, the re-zeroing technique corrects the acceleration data so that the remaining discrepancy is due to the typically small amount of the uncaptured acceleration/delta-V that occurred before wake-up ("trigger").

Like most manufacturers, in response to 49CFR563, Toyota updated their EDRs to require a 8km/h (5mph)

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Figure 12: Class 60 filtered acceleration data that did and did not result in recordings

delta-V in order for a non-deployment event to qualify for recording. As the delta-V increases, the inaccuracy due to the portion of the delta-V that occurs before "wake-up" ("trigger") becomes relatively small, as shown in the 2013 Corolla results compared to recordings from lower delta-V impacts. Interestingly, even when the ACM reported deltaV was below 8km/h (5 mph), an event was still recorded when the actual, instrumentation-based delta-V was 5mph and above.

The data translation report includes the element "Max. Longitudinal Delta-V (MPH [km/h])" as found in the "Longitudinal Crash Pulse (Table 1)" data table (example at Figure 13). The delta-V data table and accompanying graph begin at an indicated time of 0 ms ("Time Zero") with a zero delta-V value and may display the recorded cumulative delta-V data out to as much as 250ms (example data table and graph as seen in Figure 14). In the Data Limitations text for this module type, we find this passage:

is met, that ACM-evaluated event normally qualifies for recording.

For the 49CFR563 compliant Toyota system such as found in the tested 2013 Corolla (GEN3), a long-held assumption has been that a Non-Deployment is only recorded when there was a longitudinal delta-V of at least 8km/h (5mph). This requirement holds true for EDR subcomponents in other systems both used by Toyota and other auto manufacturers. For this particular module type, however, there is nothing in the Data Limitations text setting out a specific delta-V requirement for recording (specifically for recording Non-Deployments). Moreover, as seen in Figures 13 and 14 drawn from a data translation report from a GEN3 12EDR , it is clear that this module is capable of recording an event with a reported longitudinal delta-V of less than 8 km/h (5 mph).

Another unique aspect of the recorded data for this type of Toyota system is what "Time Zero" represents or where "… The data recording specifications of Toyota’s airbag (when) it's "set" at the module level inasmuch as that then ECUs are divided into the following categories. The relates to the data set as seen in Figures 11 and 12. At specifications for 12EDR or later are designed to be 49CFR563.5 we find this definition for "Time Zero:" compatible with NHTSA’s 49CFR Part 563 rule. …" "… Time zero means whichever of the following occurs (- 05012_ToyotaS02std_r028) first: Capturing as much as 250ms of longitudinal delta-V (1) For systems with “wake-up” air bag control systems, data in a data table from "time zero" and displaying a the time at which the occupant restraint control algo"Max. Longitudinal Delta-V" are functions compliant rithm is activated; or with the requirements for those data elements as found in 49CFR563. However, significant to this paper is how (2) For continuously running algorithms, the 12EDR module type reports delta-V particularly with respect to "Time Zero." The Toyota systems addressed in (i) The first point in the interval where a longitudithis study have a longitudinal "wake up"/"trigger threshnal cumulative delta-V of over 0.8 km/h (0.5 mph) is old" set at approximately 2gs and then, once that threshold reached within a 20 ms time period; or 84 Collision Magazine - Volume 16 Issue 1

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Figure 13: Recorded event with less than 5 mph magnitude for Max. Longitudinal Delta-V (MPH [km/h])

Table 2: Delta-V

Figure 14: A less than 5 mph magnitude delta-V in Table 1 Longitudinal Crash Pulse (ii) For vehicles that record “delta-V, lateral,” the first point in the interval where a lateral cumulative delta-V of over 0.8 km/h (0.5 mph) is reached within a 5 ms time period; or (3) Deployment of a non-reversible deployable restraint. …" (- 49CFR563.5) Setting aside the implications of the phrase "whichever of these occurs first," that passage should then be compared to information found in the Data Limitations text 05012_ToyotaS02std_r028 as found in the data translation report for the tested Corolla module: "… In frontal and rear collision events, the first point where a longitudinal cumulative delta-V of over 0.8 km/h (0.5 mph) is reached is regarded as time zero for the recorded data. …" (- 05012_ToyotaS02std_r028)

To find a point where a cumulative delta-V might reach 0.8 km/h, there necessarily has to be a starting place for the calculation; for the integration of the captured acceleration from some "0" point to where it reaches 0.8 km/h.

The association in 49CF563 is to a "continuously running algorithm" system which essentially means the ACM is always capturing acceleration but not necessarily calculating or "doing" anything with it until it reaches a certain trigger threshold. That trigger threshold – the normal "algorithm time zero" - for Toyota systems, is - as previously noted - 2g.

Having both the ACM reported delta-V and the reference instrumentation acceleration and delta-V provides an opportunity to evaluate the ACM’s method of setting of time zero and recording delta-V described in the data limitations text.

In light of the Data Limitations text noted above, the inclination might be to simply take the reported ACM max delta-V and add the +/- 0.8 km/h (0.5 mph) referenced as the point where, for the reported data, the module would set "Time Zero." As seen in table 2, starting with the ACM reported delta-V and then simply increasing the magnitude by 0.5 mph to that to get the "Adjusted 'ACM delta-V'" does not result in an improved delta-V correction over the regression method. This implies that the ACM reported delta-V is not simply "missing" the first 0.5 mph before Time Zero is established.

Another potential application of the data limitations text to establish the ACM’s behavior would be to find the reference or control acceleration where the magnitude first

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reaches 2gs and then where an additional +/- 0.5 mph delta-V accumulates as the ACM’s Time Zero to calculate the remaining delta-V to compare with the ACM reported delta-V. As above, processing the reference acceleration in this manner does not produce the ACM reported delta-V. However, the ACM reported delta-V does compare favorably, within 0 to 0.1 mph, with the delta-V calculated from the 2g reading. Therefore, the comparison of the reference delta-V and the ACM delta-V suggests that the ACM behaves as earlier Toyota systems and most, if not all other manufacturers’ systems, where the delta-V is captured starting at the 2g threshold. Unfortunately, application of the reporting requirement set to pick a "time zero" at the 0.8 km/h (0.5 mph) point is just that: a response to a reporting requirement and doesn't lend itself to a useful or reliable adjustment of the reported delta-V. For the module type used in the 2013 Corolla, the deltaV data table (and accompanying graph) is truncated as a function of the provisions of 49CFR563 for "end of event time" as it relates to the "up to 250ms" reporting period for, as related to this study, the recorded longitudinal deltaV. In the regulation, 49CFR563 calls for two separate but related representations of delta-V in the recorded data set.

The first is a display of the cumulative delta-V in 10ms increments (the increments represent the cumulative average over the indicated 10ms periods) from "time zero" to 250 ms or to the "End of Event Time" as further defined in 49CFR563.5. This is a reporting requirement and, particularly in light of the potential adjustments seen in Tables 1 and 2, it is reported independent of the maximum delta-V. In that respect, separately, the regulation calls for the maximum (longitudinal and lateral) delta-V as it might be captured at any point between "time zero" out to 300 ms. Obviously, the maximum might be captured after the 250 ms data table (and accompanying graph) "expires" just as it might be captured during that 250 ms period. A third related element – the time to the maximum delta-V – is then associated with the axis maximum value making clear when, relative to "time zero," the module saw that maximum value. Uncorrected then, the 2013 Corolla ACM delta-V under-reported the magnitude of both rearend and frontal impact delta-Vs by an average of 0.4 mph when compared to the maximum reported delta-V. The seemingly conflicting descriptions of delta-V and "time zero" points in the Data Limitations and the body of the report should be viewed in the context of an effort to be in compliance with the regulation (49CFR563) rather than set out the data as it might be anticipated by researchers or analysts. It might be summed up best by the ques-

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tion: who is the data ultimately for, the regulating agency or research or litigation end users?

Summary / Conclusions •

Toyota GEN1 (00 & 02EDR) and some GEN2 (04EDR) vehicles over-report rear-end delta-Vs and under-report frontal delta-Vs. This discrepancy is the result of a non-zeroed ACM accelerometer.

•

The amount of accelerometer offset, or bias, varies from vehicle-to-vehicle and even between impacts to/ with the same vehicle.

•

Acceleration re-zeroing is a technique that is generally applicable to correct delta-Vs that have been skewed by a non-zeroed accelerometer.

•

In this test series, re-zeroing the acceleration obtained by taking the derivative of the delta-V, proved to be an effective technique and typically outperformed the regression model set forth by Lee, et al.

•

The re-zeroing technique is limited to those vehicles that display a non-plateaued delta-V graph.

•

This correction could not be applied to the 06EDR and 12EDR vehicles in this study, as these vehicles did not have ACM accelerometer bias.

•

All the tested vehicles exhibited a 2g wake-up.

•

For all the tested vehicles, including the GEN3/12EDR Corolla, the ACM EDR Data reported delta-V was that which was captured in the ACM from the 2g wake threshold.

References 1. Boots K, “Toyota, Lexus and Scion CDR Coverage,” Collision: The International Compendium for Crash Research, Volume 7, Issue 1, 2012.

2. Anderson RD, “Toyota EDR Accuracy – Delta-V, Speed, etc.,” 2013 CDR User’s Summit.

3. Wilkinson C, Lawrence J, Nelson T, Bowler J, “The Accuracy and Sensitivity of 2005 to 2008 Toyota Corolla Event Data Recorders in Low-Speed Collisions,” SAE paper no. 2013-01-1268, SAE Int. J. Trans. Safety 1(2):2013.

4. SAE J211-1 Rev. July 2007, “Surface Vehicle Recommended Practice, Instrumentation for Impact Test – Part 1 – Electronic Instrumentation,” Society of Automotive Engineers International.

5. Haight R and Anderson RD, “Toyota GEN1 EDR Event Recording Logic,” Collision: The International

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Compendium for Crash Research, Volume 13, Issue 12, 2019.

6. Toyota Motor North America, publicly distributed document from approximately 2003 to 2011, "Event Data Recorder – Reference Document," specific author(s) unidentified 7. Comeau JL, Dalmotas D and German A, “Event Data Recorders in Toyota Vehicles,” Proceedings of the 21st Canadian Multidisciplinary Road Safety Conference, May 2011.

8. Testing and Analysis of Toyota Event Data Recorders,” Report prepared for North American Quality Task Force, Toyota Motor Manufacturing, Exponent Failure Analysis Associates, October 2011.

9. Ruth R, “Accuracy of Toyota Event Data Recorders,” Collision: The International Compendium for Crash Research, Volume 7, Issue 1, 2012.

10. Xing P, Lee F, Flynn T, Wilkinson C and Siegmund G, “Comparison of the Accuracy and Sensitivity of Generation 1, 2 and 3 Toyota Event Data Recorders in Low-Speed Collisions,” SAE paper no. 2016-01-1494, SAE Int. J. Trans. Safety 4(1):2016.

11. Ruth R and Muir B, “Longitudinal Delta-V Offset between Front and Rear Crashes in 2007 Yaris Generation 04EDR, “SAE paper no. 2016-01-01-1496, 2016.

12. Lee F, Xing P, Yang M, Lee J, Wilkinson C, and Siegmund G, “Behavior of Toyota Airbag Control Modules Exposed to Low and Mid-Severity Collision Pulses,” SAE paper no. 2017-01-1438, 2017.

13. SAE J1698-1 Rev April 2018, " Event Data Recorder - Output Data Definition,” Society of Automotive Engineers International.

14. Szabo, T, Haight R, Collision Reconstruction for the Medical Practitioner, Texas Engineering Extension Service (TEEX), Texas A&M University, 1998.

15. Cormier J, Gwin L, Rienhart L, Wood R & Bain C, “A Comprehensive Review of Low Speed Rear Impact Volunteer Studies and a Comparison to Real-World Outcomes,” Spine, DOI: 10.1097, PMID 29489567, ISSN 0362-2436, Feb 2018.

16. Wagner R, “A 30 mph Front/Rear Crash with Human Test Persons,” SAE Paper 791028, Proceedings of 23rd Stapp Car Crash Conference, Society of Automotive Engineers, 1979.

17. Vandiver W & Anderson RD, “Analysis of Crash Data from a 2012 Hyundai Genesis Coupe Event Data Recorder,” Society of Automotive Engineers, Paper 2021-01-0905.

18. Little DM, "Average Daily Ignition Cycles in SDMEquipped GM Vehicles," Collision: The International Compendium for Crash Research, Vol 2, Issue 2, Fall 2007.

19. Boots KE, "Ignition ‘Cyclology’ Understanding Ignition Cycles," Collision The international Compendium for Crash Research, Vol 14, Issue 2, Fall 2020.

20. “U.S. Dept. of Transportation, National Highway Traffic Safety Administration, Laboratory Test Procedure for FMVSS 208 – Occupant Crash Protection, FMVSS 212 – Windshield Mounting, FMVSS 219 – Windshield Zone Intrusion, and FMVSS 301F – Fuel System Integrity – Frontal,” Enforcement - Office of Vehicle Safety Compliance.

21. Lawrence, J, Wilkinson, C, King, D, Heinrichs, B, and Siegmund, G, "The Accuracy and Sensitivity of Event Data Recorders in Low-Speed Collisions," SAE Paper 2002-01-0679, Society of Automotive Engineers, 2002.

22. Wilkinson, C, Lawrence, J, King, D, and Heinrichs, B, "The Accuracy and Sensitivity of 2003 and 2004 General Motors Event Data Recorders in Low-Speed Barrier and Vehicle Collisions," SAE Paper 2005-011190, Society of Automotive Engineers, 2005.

Glossary ACM – Airbag Control Module AE – Algorithm Enable ATD – Anthropomorphic Test Device CDR – (the) Crash Data Retrieval (Tool) delta-V – vehicle velocity change during impact DTS – Diversified Technical Systems EDR – Event Data Recorder FMVSS – Federal Motor Vehicle Safety Standard GENn – An indication of the generation of Toyota EDR "generational groups" GEN1 being the oldest Gen4 the most recently introduced. The generations overlap. For example, "Gen1" identifies module types introduced in 2001 but may be found in vehicles built through MY '11. Gen2 systems were first introduced in MY '04 and were used in Toyotas through MY'11. Gen3 systems, introduced in MY'12 were reportedly designed to meet the requirements of 49CFR563. nnEDR – a designation of the year that a specific Toyota ACM was first introduced, for example, 06EDR was an ACM type first used starting in MY '06.

GM – General Motors Corporation Part 563 – Code of Federal Regulations Title 49 Part 563 RDS – Restraint Deployment Signal (Ford) ROT – Read Out Tool (Toyota) SAE – Society of Automotive Engineers TDAS – Tiny Data Acquisition System by DTS T0 (T0) – Time Zero VBOX – Non-contact speed data collector manufactured and sold by Racelogic

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Development of a Test Procedure for Setting Non-Deployment (ND) Events Chris Medwell, PE

Bloomberg Consulting

O

ngoing research into (1) the ND recording threshold for a particular ACM type; and (2) the accuracy and reliability of EDR pre-crash data makes the ability to repeatedly set ND events desirable. If one is to verify ND recording threshold, EDR-reported wheel speed, engine RPM, and other pre-crash parameters through testing, it is clearly advantageous to be able to set ND events without crashing into anything and without deploying expensive airbags and other restraint systems. If the intent is to assess pre-crash data, the ACM must remain connected to the vehicle that is the subject of the test when the event is triggered, which risks accidental deployments.

Literature review Hallman – Nissan SUV EDR Recording Characteristics (2020 EDR Summit) Full scale vehicle crash testing focused on Nissan ACM recording threshold and recording order was carried out by David Hallman (et al) and presented at the 2020 EDR Summit in Houston TX. Prior reports included CDR recorded ND event data from Nissan vehicles in collisions with recorded ∆V less than 5 mph – including a 2012 Versa that had recorded a collision with no longitudinal ∆V and a lateral ∆V at 1 km/h. The stated goals of the testing were to: Determine the minimum threshold for a longitudinal ND event recording, determine the event recording order and compare to the Data Limitations, and compare the findings to previously collected data.

Two types of full scale crash tests were carried out; vehicle-to-vehicle and vehicle-to-barrier. The six vehicle-to-vehicle tests involved a 2013 Nissan Pathfinder

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rear-ending a stationary Lincoln Navigator, with an incremental increase in the speed of the Pathfinder for each subsequent test. The Pathfinder was instrumented to accurately record its impact speed and ∆V for each test. After each test the ACM was downloaded to check whether the collision had been recorded. Test results found that vehicle-to-vehicle frontal impacts with impact speeds from 3 to 4.6 mph and ∆V’s up to 3.9 mph were not recorded by the ACM. The final test with a 6.2 mph impact speed and a -5.3 mph ∆V (per the instrumentation) was recorded in the ACM at -4 mph.

In six frontal impacts with the concrete barrier, the Pathfinder did not record events with ∆V’s up to -4.9 mph but did record the last two tests which both showed ∆V’s at -5.5 mph. In three rear impacts with the barrier, a longitudinal ∆V at 4.9 mph was not recorded by the ACM. The last test with an impact speed of 5.1 mph and a ∆V at 6.5 mph was recorded in the ACM as 5 mph.

While the Hallman testing verified the 5 mph ND event recording threshold for the test vehicle, further research into the ND recording threshold for other Nissan vehicles is suggested in order to understand the known examples of Nissan vehicles having recorded events with ∆Vs below that threshold.

In order to create 4 recorded ND events in the ACM, Hallman had to source two vehicles, concrete barriers, a test facility and instrumentation, and carry out 15 vehicle crashes. At the conclusion of the testing, the cost to repair the test vehicles had been incurred or absorbed. Clearly, there is a research need to create ND recorded events, whether it is to verify pre-crash data, recording thresholds, or event recording order. A

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reliable method of creating these events without actually damaging the test vehicles could enable more costeffective research into these subjects.

Bosch CDR Software Instructions for Bench Downloading “EDR Data Volatility” “When imaging EDR data with airbag control modules (ACM) or other ECUs removed from the vehicle with an EDR, always make sure that while the CDR Interface Module is connected to the ECU that it is sitting level, in

its upright position and does not get moved, turned over or dropped.”

“While the CDR System is not capable of writing data to an ACM or ROS, when an [sic] either one are powered up using the CDR System, particularly when imaging them out of the vehicle, it may be possible to create a situation where the data stored in an event may be replaced with "data" stored during rough handling of an unsecured and powered up ECU. ACMs or ROS’s [sic] which are not adequately secured while powered up should always be treated as though the data is volatile and they should be powered down and left to discharge any stored electrical

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power for at least 2 minutes after power is removed from the CDR Tool. Note that for Roll-Over Sensors or ACMs with roll-over sensing, the ECU is very likely to set an event if it is turned over when powered for up to 2 minutes even after power is removed.”

From (typical) Chrysler Data Limitations: “CAUTION: During direct-to-module imaging where the Airbag Control Module (ACM) is disconnected and removed from a vehicle, make sure the ACM is not moved, tilted or turned over while connected to and powered by the CDR Interface Module (with appropriate adaptors in place, where required). Also, after a CDR imaging process, wait 2 minutes after power is removed from the ACM before attempting to move the module. Not following these general ACM guidelines for direct-to-module imaging may cause new events to be recorded in the ACM." We are told to secure the ACM by clamping it, lest we inadvertently set a new (non-deployment or deployment) event. There are anecdotal stories of dealership repair technicians accidentally deploying airbags in the shop. Clearly, if the ACM is powered up, a sharp impact to the ACM and/or dropping it has been known to cause unintended events.

events will now occur inside the ACM and not get recorded without reaching that 5 mph ∆V, the mallet method risks increasing effort with the mallet until a deployment occurs, as happened to Vandiver & Anderson.

Even though Vandiver & Anderson deployed an airbag, the recorded ∆V (-1 km/h) was nowhere near 5 mph.

Hence, Vandiver & Anderson were not even close to their stated goal of setting an ND event, no matter how hard the mallet strike. The deployment decision in Anderson’s case was based on a large initial impulse in the first 10 msec but the limited available movement of the ACM ultimately resulted in a trivial ∆V. Test Development Goals If the ACM has to see a 5 mph ∆V before an ND event will be set, the test method will have to achieve that ∆V without creating the large initial impulse that can cause a deployment decision. If this is to be done without crashing the vehicle, then the ACM speed with respect to the vehicle will have to change by about 5 mph. This requires movement of the ACM. How much movement is required? That depends on how much acceleration you can impart. For example, to accelerate at 0.5 g to 5 mph we have:

In the CDR data from some early GM SDM’s, the ignition cycles “at event” were given but not the ignition cycles “at download”, leading to questions regarding whether the recorded event was indeed the collision of interest. This led some to attempting to “set” a new event by sharply impacting the powered-up ACM. The newly set event would Or, using the rounded off “slide to stop” formula: then report the current ignition cycle count. As long as the ACM was not connected to a vehicle, there was no danger What if the ACM is accelerated faster? From Part 563, the of actually deploying airbags. algorithm enable threshold is 0.5 mph within 5 msec , or Collision Magazine (Volume 14 Issue 1) Airbags, Myths, about 4.5 g. Therefore, a tester can plan to accelerate the Legends, and Lore by Wesley Vandiver and Robert Ander- ACM at perhaps 1 to 3 g’s without setting an event, then son. stop it abruptly in order to set the event. If you could accelerate it at 2 g, for example, you could get it to 5 mph in The authors were attempting to set a non-deployment 5 inches. event by “loosening slightly” the mounting nuts of the ACM “affording some movement forward” and striking it At 5 g, you are in the algorithm enable range, but if your with a mallet. As we shall see, this method was doomed acceleration gets too high you risk setting off a deployment to fail.

(Vandiver & Anderson recorded 1 km/h in 2.5 msec which would be about 11 g). To reliably accelerate the ACM to Back in the days before the “8 km/h or 5 mph ∆V within get it to 5 mph without causing a deployment command is 150 msec” ND recording threshold mandated for MY going to require several inches of ACM movement. Hence, 2013 vehicles, any event that resulted in algorithm wakemerely loosening the ACM mounting screws, allowing up was recorded. With no minimum ND event recording perhaps ¼ inch of movement, is not nearly enough. Any threshold, the mallet strike method, or just banging the testing that hopes to reliably set ND events will likely remodule on the table could be enough to wake up the modquire a repeatable acceleration over several inches of moveule and thereby set an event. As mentioned, people have ment of the ACM. done this sort of thing in bench tests just to get the current ignition cycle count. However, since these trivial ND 92 Collision Magazine - Volume 16 Issue 1

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Mindful of the risk of setting a deployment event, it may also be important not to stop the motion of the ACM too rapidly. The onset of the airbag algorithm may require accelerations exceeding the Part 563 threshold, but the Anderson airbag deployment shows the risk of accelerations in excess of what is needed to set the algorithm going. Hence, the test fixture needed to be repeatable, able to impart similar accelerations to the ACM during each test, and to gradually increment the acceleration upward until the ND recording threshold is met.

However, by remounting the ACM vertically (See Figure 3) more ACM movement was made possible without extending the wire harness to the ACM.

Test Apparatus The vehicle used for testing was a 2018 RAM ProMaster 1500 van. This vehicle was chosen for this testing because we had reason to suspect that the pre-crash speeds on a similar van were being reported incorrectly (see separate article). See Figure 1.

Figure 1: 2018 RAM ProMaster 1500 Van We began by removing the interior trim to expose the ACM and its wiring harness. By cutting some zipties securing the ACM wiring to the vehicle, we were able to allow some limited horizontal movement of the ACM while still connected to the wiring. It would be possible to install additional wiring length in order to extend the available horizontal movement. (See Figure 2).

Figure 2: ACM in wooden sled, mounted horizontally

Figure 3: ACM in wooden sled, mounted vertically We fabricated a wooden sled base bolted to the ACM and mounted within a sled platform with available ACM movement of approximately 7 inches. In order to increase our available ACM acceleration rate to over 1 g, and to accommodate the movement without needing to install extra wiring, we elected to test using a vertical ACM orientation.

The forward arrow marked on the ACM was facing the floor of the vehicle. In its resting condition, the top (back) of the ACM was secured to the bottom of the fixture with elastic cord and holes were drilled at ½ inch intervals up from the base of the fixture. For each test, the ACM was pulled upward against the elastic cord to a point where a pin was inserted through the fixture to hold the ACM at the test height. (See Figures 4, 5, 6 and 7). The vehicle was driven at a known speed, and the pin was pulled out, allowing the ACM to fall the test distance. If the test distance did not create a recorded event, then the test distance was increased for the next test. At the test height of 6 inches, we began to see recorded ND events. We were able to repeatedly create ND events at 6 inches, although in later testing we went up to 6 ½ inches, perhaps as the elastic cord wore out.

Figure 4: Front view of the test apparatus

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Test Results We created a total of 9 ND events using the test apparatus.

Some results were not what we expected and may appear counterintuitive. For example, with the forward surface of the airbag module impacting the base of the test fixture, we expected the events to be recorded as frontal events and with negative ∆V. The reported events were all positive ∆V. It is not clear whether the vertical test orientation affected the polarity of the recorded data. (See Figure 8).

Figure 5: Rear view of the test apparatus

In addition, the ND events were all recorded with ∆V below the stated recording threshold of 8 km/h or 5 mph.

Instead, most of the ND events showed a maximum ∆V at +6 km/h but at least one ND event showed only 5 km/h so it appears the recording threshold of the module tested was 5 km/h or about 3 mph. An example of the data recorded during one of the tests is shown in Figure 9.

As an exercise, we can look at the approximate 5.5 km/h (5 fps) speed to which we apparently accelerated our ACM over 6 inches and we see that our achieved acceleration rate was less than 0.8 g, despite the downward force of the elastic cord and gravity. We were fortunate to have found an ACM with the lower recording threshold; otherwise our available 7 inch test drop distance may not have been sufficient to create recorded ND events.

Once the ACM reached the bottom of the test fixture, the recorded event showed accelerations generally at the rate of 1 km/h in 8 to 10 msec, with the accumulated ∆V reaching 5 km/h in about 50 to 60 msec. A change of 1 km/h in 8 msec is about 3.54 g.

Recommendations for Future Testing

Figure 6: ACM in forward position

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While the vertical test orientation allowed us to increase the available ACM acceleration rate and avoid having to modify the vehicle wiring to allow the movement distance needed, it introduced doubt as to whether the non-standard orientation affects the recorded ∆V (not the pre-crash data). Further testing would be required to verify the apparent 5 km/h recording threshold for this ACM. ACM’s with the higher 5 mph recording threshold would not be expected to record an event at the 6 to 8 inch test distance, even vertically. Horizontal testing to a 5 mph recording threshold would be expected to require more ACM movement than 8 inches. The acceleration of the ACM would not be gravity-assisted and would depend solely on the elastic cord or some other device (hydraulics anyone? ).

Also, there would be increased friction between the ACM sled mount and the sled platform, which may be mitigated by using lubrication, rollers or some other method of allowing horizontal motion with reduced friction.

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Figure 8: Bosch CDR ND event data from testing 2018 RAM ProMaster 1500 Van

Figure 9: Bosch CDR longitudinal ∆V graph from testing 2018 RAM ProMaster 1500 Van In future testing, the authors would recommend constructing an extension to the wiring harness to accommodate horizontal movement of the ACM of at least 12 to 18 inches. The sled mount for the ACM should move as freely as possible, since accelerations in the 1 to 2 g range may be required. The test fixture should allow gradual increments in acceleration rate, acceleration distance, or both: the use

of elastic cord and drilled holes as in our testing would be feasible, but the ability to add strength or number of elastics may be required to achieve the needed acceleration rates. Other designs might utilize coil springs between the sled mount and the sled platform to propel the ACM.

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

Robert Anderson

Collision Forensics, Inc.

Biomechanics Analysis

Event Data Recorder Delta V: The Effect of Tire Friction

I

n addition to the constantly evolving Event Data Recorder technology, Toyota Vehicle Control History, Tesla diagnostic logs, GM Advanced Safety data, Subaru Eyesight, Berla iVe, etc. electronic data from automobiles is ever expanding and has become ubiquitous in motor vehicle crash investigation.

While computers do not lie or exaggerate, there are circumstances when their recordings can be misinterpreted as to what they represent in the physical world. For example, it is well understood that skid, spin, hydroplaning, being airborne, etc. can result in pre-crash speeds that do not represent a vehicle’s actual over-the-ground speed. Similarly, in some circumstances to arrive at the actual collision force between vehicles and/or the ∆V to which vehicle occupants were subjected, the friction between a vehicle’s tires and the roadway must be accounted for.

In order to properly apply Newton’s Laws, a tool known as a free body diagram, can be used to account for all the forces acting on an object by replacing an objects contacts with the forces exerted. Figure 1 shows the free body diagram for the Impala.

Conceptually, the Impala shown in Figure 1 is being decelerated by both the crash force Fc from the collision, and the frictional force Ff from continued hard braking and skidding during the impact. The frictional force is, Ff = W * Cf, the product of the normal force, which is the vehicle weight, times the coefficient of friction, or drag factor, between the tires and the roadway. Netwon’s 2nd Law, states that the net force, or the summation of forces is, ∑F = m a, the mass times acceleration. Average acceleration can be represented by ∆V/∆t, the change in speed divided by the collision duration. Therefore, substituting and rearranging, we get: 96 Collision Magazine - Volume 16 Issue 1

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∆Vtotal = (Fc + Ff ) ∆t / m ∆Vtotal = (Fc ∆t / m) + (Ff ∆t / m) ∆Vtotal = ∆Vc + ∆Vf Therefore, in this example the total Delta V of the Impala is the Delta V due to the collision force plus the Delta V due tire friction from hard braking and/or skidding.

Another example is shown in Figures 2 and 3 where a Grand Marquis skid through an impact with a Honda CBR so that ∆Vtotal was a combination of the speed change due to skidding, plus the ∆Vc. This is shown graphically in Figure 3 where the acceleration shows the slowing that is the result of braking plus the superimposed slowing due to the collision.

The two crash tests above are examples of how the tire friction from the bullet vehicle’s braking increases the Delta V experienced by that vehicle during the impact, and as measured by that vehicle’s own accelerometer within its airbag control module.

Revisiting the first example, the free body diagram for the Corolla shown in Figure 4 illustrates how the net force acting on the struck vehicle is the collision force minus the frictional force. In other words, the friction of the struck vehicle’s tires on the roadway reduces the net force and therefore the resultant or ∆Vtotal.

In 1990, Emori and Horiguchi set forth momentum equations with an impulse term to account for the friction between the tires and the roadway of the struck vehicle.[1] These equations were presented again in a 1998 paper in which the momentum equations were rearranged in terms of vehicle ∆V as shown in Figure 5.[2] With the impulse

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Figure 1: SATAI 2022 Test 6 Impala broadsiding a Corolla (Impala’s free body diagram)

Figure 2: IATAI 2019 motorcycle class Test 1 – Grand Marquis vs Honda CBR momentum equations written in this way, it can be seen how the impulse term from tire friction of the struck vehicle (∑Fext ∆t) decreases the struck vehicle’s ∆V while increasing the striking vehicle’s ∆V. Figure 5, conservation of momentum with an impulse term for tire friction on struck vehicle, where ∆V1 and ∆V2, are the Delta V’s of the bullet and target vehicles, m1 and m1, are the masses of the bullet at target vehicle, Vc is the closing speed, ∑Fext is the net external force from friction, and ∆t is the collision duration Indeed, the crash tests results presented in the 1998 paper not only showed a decreased target vehicle ∆V and increased bullet vehicle ∆V but the collision duration of the target was also decreased while the bullet vehicle’s collision duration was increased. Initially this might seem counter-intuitive. However, if the tire friction force is thought causing an offset to the vehicle’s acceleration, similar to that observed in early Toyota ACM’s due to

Figure 3: the Grand Marquis’ speed and acceleration

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Figure 4: SATAI 2022 Test 6 Impala broadsiding a Corolla (Corolla’s free body diagram) non-zeroed accelerometers, it can be seen how shifting the acceleration pulses down could increase the bullet vehicle’s acceleration and duration, while reducing the target vehicle’s acceleration and duration, as illustrated in Figure 6.

In many EDR reports, the pre-crash deceleration from the bullet vehicle’s braking is evident in its pre-crash data. For frontal impacts, the occupant kinematics would only produce greater driver braking, so it is fair to expect similar or greater braking during the impact. For a typical collision duration of 1/10th of a second, and with a coefficient of friction or drag factor of 0.75, the ∆V from tire friction is the same as the speed change from skidding over a tenth of second which can be calculated as, 0.75 * 32.2 ft/sec2* 0.1 sec * 3600 sec/hour/(5280 feet/mile) = 1⅔ mph.

While a 1⅔ mph ∆V might seem insignificant for the analysis of many collisions, in low speed impacts, and situations where there is a large weight difference between the vehicles. For example, when using conservation of momentum to estimate a motorcycle’s impact speed using the

Figure 5: Conservation of momentum with an impulse term for tire friction on struck vehicle

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lateral ∆V reported by the target vehicle’s airbag control module, neglecting friction of the target vehicle would produce a gross under-estimation of the motorcycle’s actual impact speed. Similarly, the effect of vehicle braking provides an explanation for the unrealistic EDR reported ∆V observed in some pedestrian collisions.

References 1. Emori RI & Horiguchi J, “Whiplash in Low Speed Vehicle Collisions,” SAE paper 900542.

2. Anderson RD, Welcher JB, Szabo TJ, Eubanks JJ & Haigh WR, “Effect of Braking on Human Occupant and Vehicle Kinematics in Low Speed Rear-End Collisions,” SAE Paper 980298.

Figure 6: the effect of target vehicle braking on bullet and target vehicle accelerations [2]

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or g Cr an as iz at h Te io st nal in g

The 2021 and 2022

SATAI Crash Program

Robert Anderson Biomechanics Analysis

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The Southwestern Association of Technical Accident Investigators (SATAI) is a non-profit training organization that typically offers two conferences per year. Both conferences have two days of classroom training, which count toward ACTAR CEUs. Once a year the conference includes a crash program, which is held at the Glendale Regional Public Training Center in Glendale, Arizona. As shown in Figure 1, the facility has a 500 by 800-foot test pad, which can accommodate a wide variety of vehicle handling and crash test demonstrations.

The SATAI crash program went forward in 2021 though there were not conference meetings and the 2022 SATAI Crash Conference was held February 18-19.

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Figure 1: Google Earth Aerial Image of the Glendale Regional Public Safety Training Center Of the following 14 vehicles that were used in the two-year crash program, only the Thunderbird and the oldest Civic were not Bosch CDR supported.

2014 Nissan Sentra

verification crash tests. The Honda was occupied by an instrumented human driver, and the Subaru was occupied by a human driver with instrumented right front and right rear volunteers.

2013 Hyundai Genesis

2012 Honda Civic coupe 2015 Chevrolet Sonic

2005 Chevrolet Astrovan 1997 Ford Thunderbird

2003 Chevrolet Suburban 2013 Honda Civic sedan 2015 Hyundai Elantra

Figure 2: a 2012 Honda Civic sedan front-to-barrier impact (Preconference Test 5)

2013 Subaru Outback

2003 Honda Civic sedan 2006 Chevrolet Impala 2007 Chevrolet Impala 2005 Toyota Corolla

The 2022 SATAI Crash Conference featured pre-conference front and rear-to-barrier crash tests using a Honda Civic sedan and a Subaru Outback. Reference instrumentation measured pre-crash and crash data to allow comparison with the EDR data from two Bosch CDR supported brands for which there has been no known previous EDR 102 Collision Magazine - Volume 16 Issue 1

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Figure 3: a 2012 Honda Civic sedan rear-to-barrier impact (Preconference Test 7)

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The Subaru test series concluded with a 16 mph rear-end impact from a 2005 Toyota Corolla, driven by an instrumented driver. The Subaru had an instrumented driver and left rear passenger volunteers.

Finally, the results of an oncoming side-swipe between the 2002 Honda Civic and the 2005 Toyota Corolla is included in the 2022 SATAI Crash Conference data package.

The 2022 SATAI Crash Program

Figure 4: a rear-to-barrier impact with a 2013 Subaru Outback (Test D)

Figure 5: a front-to-barrier impact with a 2013 Subaru Outback (Test E)

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 and biomechanical 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, neck and lumbar load cells in the anthropomorphic test device (ATD), 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-bard high speed video.

Crash Demonstrations 1 and 5 were both 13 mph closing speed rear-end impacts between matched Chevrolet Impala’s with instrumented human drivers and an instrumented rear seat ATD. After the first crash, the striking vehicle was stationary and rear-ended by the target vehicle from the first crash after the driver’s switch positions and the ATD was moved from one vehicle to the other. This data set enables one to make a one-to-one comparison of vehicle, human driver and ATD passenger kinematics from matched vehicle impacts with different impact speeds but the same closing speed.

Crash Demonstrations 2 and 3 involved a 2012 Honda Civic sedan that was remote driven by the Phantom Driver into a Rescue Randy on an E-Scooter.

Figure 6: 2013 Subaru Outback rear-ended by a 2002 Honda Civic (Test K)

Crash Demonstration 4 was on offset rear-end crash between the Phantom Driven 2012 Honda Civic and the 2002 Honda Civic. As shown in Figure 9, the target vehi-

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Figure 7: 2006 Impala rear-ended by a 2007 Impala while both vehicles moving (Test 1)

Figure 8: Rescue Randy on E-scooter struck by a Phantom Driven 2012 Honda Civic (Test 2)

Figure 9: Offset rear-end with Phantm Driven 2012 Civic and 2002 Civic (Test 4) cle’s trunk opened and the right front tire debeaded (dust cloud at vehicle’s right front).

The conference crashes concluded with an angled broadside between a human driven Chevrolet Impala into the 2005 Toyota Corolla

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Figure 10: Angled broadside between human driven 2007 Impala and 2005 Corolla (Test 6) SATAI 2021 Crash Program 2021’s crash program consisted of instrumented EDR verification testing using a 2012 Hyundai Genesis, a 2013

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Figure 11: Head-on with human driven 2012 Genesis and 2002 Civic

Figure 12: Human driven 2015 Elantra into and 2015 Sonic into 1997 Thunderbird (test 16) Nissan Versa, and a 2015 Hyundai Elantra in vehicle-tobarrier and vehicle-to-vehicle crashes. The Hyundai EDR verification testing was concluded with a human driving the Genesis head-on into a Chevrolet Astrovan at 25 mph and a human driving the Elantra into a 2015 Chevrolet Sonic at 31 mph, which went forward into a 1997 Ford Thunderbird in a 3-car rear-end configuration.

Finally, the data set from the 2021 SATAI crash program includes lower speed three car rear-end impacts between the Elantra, Sonic and Thunderbird, as well as angled broadside and angled frontal impacts with ATDs seated in

the Elantra’s right front and right rear seats, and skid testing with bumper height changes.

Acknowledgements Thanks to the support and generosity of SATAI, the Glendale Police Dept. and our crash team, which includes: RSR Engineering, Aperature, Hallman Engineering, Billy Cox Group, Forensic Injury Analysis, Case Study Collision Science, 4N6XPRT Systems, Forensic Science and Biomechanics, Accident Science, Collision Forensics, Deta B, Biomechanics Analysis, and many others.

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Case Analysis Solution:

CA SE So lu PRO ti BL on EM

Discovering and Explaining a CDR Data Anomaly Chris Medwell, PE

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A

man astride a Harley-Davidson motorcycle was stopped at an intersection (waiting for oncoming traffic to clear so he could make a left turn) on a straight, level rural roadway with a posted speed limit of 55 mph when his motorcycle was struck from behind by a 2018 RAM ProMaster van. The collision was recorded within the van’s Airbag Control Module and the EDR data was retrieved using the Bosch CDR Tool software (version 17.9.1) as a non-deployment (ND) event record. The event record included 5 s of Pre-Crash Data that reported that the van had approached at a steady speed of about 20 mph.

The van’s driver told police that she had not seen the motorcycle. There was no heavy traffic, construction, other slow-moving vehicle, inclement weather, or any other reason why the van would be going 20 mph on a 55 mph highway. Witnesses told police that they thought the van had been traveling at about the speed limit and did not appear to have braked prior to impact. The motorcyclist was ejected during the collision and his head came into contact with the van’s windshield. (See Figure 1).

feet to stop following this collision? Calculate the post-impact speed of the van if the van was in fact braking hard for 50 feet post-collision.

The CDR-reported speed of the van at (up to 0.1 s prior to) impact was 18 mph. Its maximum longitudinal ∆V is reported under System Status at Event as -6.8 mph (11 km/h) at 176 msec, and matches the data in the Longitudinal Crash Pulse table, which reaches -11 km/h at 176 msec and remains at that level for the rest of the data. The lateral ∆V is small enough to ignore in this aligned, inline collision. Therefore the post-impact speed of the van should be 18 mph – 6.8 mph = 11.2 mph (or slightly less). Use your favorite slide-to-stop formula to determine that (assuming 0.7 g drag factor) the van should stop in less than 6 feet of braking after impact. Using the same drag factor and assuming braking for 50 feet post-collision, the van’s post collision speed would have been 32.3 mph. Finally, the same slide-to-stop formula should tell you that if it takes 50 feet to stop from 11.2 mph the drag factor is about 0.084. (Is a drag factor of 0.084 consistent with skid marks at the scene?)

Question 2: Calculate the ∆V for the motorcycle/ rider combination based on the CDR-reported ∆V for the van.

Figure 1: Bloomberg Consulting photograph showing van front end damage Solutions Question 1: Calculate the post-impact speed for the van based on the CDR-reported column titled “Speed, Vehicle Indicated” of the van and its recorded ∆V. Use this post-impact speed to estimate the required post-impact braking distance for the van to come a stop after the collision. Compare this distance to the 50 feet of maximum braking marks evident at the scene. What braking deceleration rate would be required for the van to take 50

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Again, the van’s maximum longitudinal ∆V is reported under System Status at Event as -6.8 mph.

The van curb weight was 4776 lb and the motorcycle dry weight was 690 lb. For the purpose of our calculations we will add 200 lb to each vehicle to account for the driver and contents. The motorcycle’s ∆V is a positive value, since it was struck from the rear. So the equation becomes:

What stands out like a sore thumb in this calculation is this: if the van was only going 18 mph at impact, how could the motorcycle sustain a +38 mph ∆V? Hence, we have the next question: Question 3: Calculate the expected impact speed for the van based on the motorcycle and van ∆V’s determined in Question 2. Does anything stand out about the result of these calculations?

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We have the weight of the van at 4976 lb, the motorcycle at 890 lb, and the relevant ∆V’s are -6.8 for the van and +38 mph for the motorcycle. We also have the motorcycle’s pre-impact speed at zero. Neglecting restitution, the van’s speed post-impact is the same as that of the motorcycle.

This requires the van’s speed to be 38 + 6.8 = 44.8 mph at impact. Accounting for typical restitution e (ranging from about 0.1 to about 0.3 in vehicle impacts with the highest values for restitution in the lowest speed impacts), lower van impact speeds can result in the same ∆V. Per Schmidt, et al., solving for closing speed (which in this case since the motorcycle was stopped equals the speed of the van)

1st gear speed: 2nd gear speed: 3rd gear speed: 4th gear speed: 5th gear speed: 6th gear speed: To the extent there is transmission torque convertor slip, the speeds would be lower but they could not reasonably be higher than calculated above. So which gear was the van in at an indicated 19.3 to 19.9 mph? The answer: is there isn’t one. There’s no gear that could result in a calculated speed equal to or slightly above 19.9 mph. 3rd gear is not enough, and 4th gear is too much.

Moreover, we suspected that, even if some combination of tire size, speedometer calibration error or incorrectly reported gear ratios would allow the van to go 19.5 mph in any gear at 1696 RPM, the automatic transmission calibration would not maintain that RPM for several seconds in steady state at 10% throttle opening.

The same formula can be rearranged to calculate the expected ∆V for the van if its impact speed was 18 mph. For restitution values between 0.1 and 0.3 the ∆V calculated for the van is -3 to -3.5 mph, around one half of the reported value of -6.8 mph.

Question 4: Assuming that the Pre-Crash Data reported within the (version 17.9.1) CDR report is correct, what gear would the van’s transmission have been in prior to the brake being applied?

From the Pre-Crash Data we see 1696 RPM recorded and the displayed speed at 31 or 32 km/h (converts to 19.3 mph or 19.9 mph, rounded to the nearest whole mph in the data table). The formula for road speed based on engine RPM is:

In this case for 1696 RPM (assuming no transmission torque convertor slip): 108 Collision Magazine - Volume 16 Issue 1

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Why would a modern van rev up to 1700 RPM when traveling only 20 mph – wouldn’t the transmission just upshift to a higher gear? Of course, it would. It would upshift to a higher gear to drop the RPM and save fuel.

Question 5: Based upon the results of the above exercise, do you see any issues with the CDR-reported data for this collision? If there is an issue, how would you explain the data to your client?

This case presented a data anomaly which can be summarized as an inconsistency between the CDR-reported wheel speeds for the ProMaster van in the Pre-Crash Data tables and the van’s recorded ∆V. Simply put, if the PreCrash Data table speed was correct, then the ∆V was about double what would be expected. If the ∆V was correct, then the Pre-Crash Data table speed was about half of what would be needed to create the reported ∆V. So, if both values cannot be correct, what evidence indicates whether either one is correct? In question 1 we found the roadway evidence (i.e. braking with visible tire marks for 50 feet after impact) suggests that the post-impact

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speed is 32 mph and therefore the impact speed cannot be 18 mph but would most likely be in the 39 mph range if the recorded ∆V is correct. The slide-to-stop calculation is an assessment of the kinetic energy. In questions 2 & 3, we used momentum techniques to determine that an impact speed in the 35-40 mph range would comport with the recorded ∆V as well. In question 4 we found that the van cannot travel at 20 mph at 1696 RPM, but it can travel at 40 mph (in 5th gear) at that RPM. So from energy considerations, momentum considerations, and from engine RPM analysis, the consensus is that the CDR-reported speed was about half of the correct speed.

hicle network. All testing was video recorded showing all instrumentation. This enabled comparing both the speedometer display speed and the speed on the OBD2 data bus to the known speed from the GPS while driving the van.

Testing

became clear that the CDR-reported pre-crash speed as retrieved from the recorded data in this module type was translated at approximately 50% of the correct or actual speed. The testing data and findings were made available to both Bosch and FCA. Bosch verified that their translation of the raw data followed the instructions they received from FCA. After investigating the issue, FCA discovered that the ACM module supplier spec sheet data for this module type was incorrect and the raw data was, in fact, being reported at 50% of the true value (see Figure 2).

In this phase of testing, we disconnected the front wheel speed sensors one at a time and discovered there was no effect on either the speedometer display or the OBD2 data bus speed. This seemed contrary to the CDR data limitations indicating the CDR-reported pre-crash speed was the average of the two drive (front) wheels. Next, we disconnected each rear wheel speed sensor individually and discovered that disconnecting the left rear wheel Why would the CDR Pre-Crash Data table report vehicle speed sensor had no effect, but disconnecting the right rear speed at half of its true value? We knew that FCA products wheel speed sensor rendered both the speedometer and the generally had done away with dedicated vehicle speed sen- OBD2 speeds to 0. This indicated that the OBD2 speed sors in favor of using the ABS wheel speed sensors. The signal was properly displayed on the speedometer but was Data Limitations section in the CDR report, which used not from the drive wheels and was not the average of two standard language common to US-built FCA products, wheel speed sensors. stated that the recorded speed was the average of the wheel speeds of the drive wheels. Unlike some CDR reports from We developed a repeatable method (see separate article in other FCA vehicles, the individual wheel RPMs were not this issue of Collision: “Development of a Test Procedure for Setting Non-Deployment (ND) Events.”) for creating reported in the data.

ND events within the airbag control module. Using this Ultimately, we had two theories that could explain the method, we discovered that with all four wheel speed sendata. One theory developed was that that the van involved sors functioning, the CDR-reported pre-crash speed was in the crash had malfunctioning wheel speed sensor(s). As- half of the speedometer display and OBD2 speeds at the suming the CDR-reported pre-crash speed was the average time of the event. It appeared that the Bosch CDR softof the two drive wheels (in this case the front wheels), if ware was “expecting” to receive and then average the data one of those two sensors reported a zero value, the CDR- from two wheel sensors, but it was actually dividing the reported speed could be half of the true value. The oth- value reported by the one sensor by two. The second theer theory, which we believed was less likely, was that the ory, a software translation issue, turned out to be correct.

CDR-reported pre-crash speeds were somehow translated or converted from wheel speed sensor signals incorrectly Conclusions by either the software in the vehicle (which should affect Bloomberg Consulting's testing demonstrated that, for the the speedometer reading as well as the CDR data) or with- 2018 Ram ProMaster van, the speedometer display and in the CDR program. We had to do testing to discover the OBD2 data bus speeds were not averaged from two drive reason for and the nature of the data anomaly: is it the soft- wheels, as stated in the Data Limitations, but were generware in the vehicle or the software in the CDR program? ated from a single non-driven wheel speed sensor. It also For testing, we utilized a similar 2018 Ram ProMaster van purchased for that purpose. In road testing, we confirmed that the van does not maintain 1700 RPM steady-state at speeds below 20 mph – it upshifts to a higher gear. However, the van could be driven at 40 mph steady state at 1700 RPM in 5th gear, as the transmission tended to shift up to 6th gear at a slightly higher speed. In order to understand the source of the vehicle speed data, we equipped the van with a Garmin GPS to display travel speed independently of the van’s electronics, as well as a Zurich ZR13 OB2 Code Reader. The ‘live data’ feature of the OBD2 device was used to monitor the vehicle speed from the ve-

A subsequent CDR Tool software update (version 21.0) described the error correction in the "What's New (in this

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version of the CDR Software) section of the Help file as follows: •

Changed display requirement for "Speed, Vehicle Indicated" for 2018 and newer ProMaster

And what else does your EDR instructor tell you about this? MAKE SURE YOU ALWAYS TRANSLATE CDR DATA USING THE LATEST VERSION OF THE SOFTWARE. A comparison of the data generated from the corrected CDR version 21.1 to the initial version 17.9.1, can be seen in Figures 2 and 3 at the end of the article.

software release. In the case of 2018 and newer RAM ProMaster, the CDR file in software versions prior to version 21.0 will report 50% of the actual vehicle pre-crash speed.

We should note that the language regarding the source of the vehicle indicated speed being an average of the drive wheel speeds is unchanged in CDR software version 21.

See following pages for excerpts from the latest version of the vehicle CDR report at print version 21.3.

Footnote: [1] 1 Schmidt, B. F., Haight, W. R., Szabo, T. J., and Welcher, J. B., “System-based energy and momentum analysis of collisions,” technical paper Although substantive changes to the translated/reported 980026, Society of Automotive Engineers, Warrenpre-crash wheel speeds like this are, thankfully, going to be dale, PA, February 1998, found in "Accident Reconvery rare, until you check, you never know what changes struction: Technology and Animation VIII SP-1319 might have been made as part of the newest CDR Tool

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Figure 3: Bosch CDR (Version 17.9.1) Pre-Crash Data table (2018 RAM ProMaster 1500 van)

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Tesla EDR Tool Kit

EDR Data can be retrieved from all Tesla Model S, Model X, Model 3, and Model Y vehicles. Tesla Roadster, which was produced from 2008 to 2012, is equipped with a RCM but does not have an EDR.

The EDR Retrieval Hardware Kit for Tesla vehicles contains all the hardware required to download the Event Data Recorder (EDR) data that may be stored in all Tesla Model 3, Model S, Model X, and Model Y vehicles. This is the only kit that contains genuine Tesla EDR cables.

Available at Crash Data Group www.crashdatagroup.com (800) 280-7940 crash@crashdatagroup.com

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Expert AutoStats®

4N6XPRT BioMeknx™

Expert AutoStats® is a computer program containing over 50,000 vehicles cars, vans, utility vehicles, and light pickups. 1945-2020 model years are represented.

(Laptop & Desktop Windows 32 & 64-bit OS Compatible)

Enter:

Manufacturer and Year

Select:

Model from pop-up window

Output:

Wheelbase Overall Length Height Wt. Distrib

Curb Weight Width Drive Wheels Front/Rear Track

Mid-60's to present output also includes (when available): Front Overhang Rear Overhang Bumper Heights Hood Height Turning circle Wheel radius Bumper-to-Hood Bumper-to-Window

Expert AutoStats® is currently owned by over 700 private individuals and 300 Law Enforcement agencies in the U.S.A., Canada, and South America. Additional information, brochure, and order from can be downloaded from:

www.4n6xprt.com/4n6as.htm

4N6XPRT StifCalcs® 4N6XPRT StifCalcs puts the NHTSA Crash Test database on YOUR 32 or 64 bit MS-Windows computer PLUS calculates A-B-G values and Test Specific Crush Factors based on the NHTSA test data, with no need for you to get on the internet, all for the price of only $700.00*!

Can you do this yourself “for free”?? Only if you value YOUR time at $0.00!!

4N6XPRT BioMeknx is designed as a collection of the Biomechanical data of importance to the Accident Investigator into one easily accessible reference location. It is designed as a program to be useful to ALL accident investigators, not just the Biomechanical expert.

The program includes: 1. Over 65 printable illustrations and charts 2. 10 Separate categories or sections of information related to forensic biomechanics 3. Information on walking speeds of people from 17 months to > 65 years 4. Calculation modules for: - segment length from total body height, - segment weights and Centers of Mass (CoM) based on total body weight, - Predicted Maximum Walking Speed based on total height 5. Information was obtained by review of over 65 scientific texts, several of which are now "out of print"

www.4n6xprt.com/4n6bm.htm PROGRAM ORDER FORM (Please Print) Contact Name: ________________________________________________ Company: ____________________________________________________ Street: ______________________________________________________ City:____________________ State:____ Zip:__ __ Country: __________ Phone: (_____) _______________ Fax: (_____) ___________________ E-Mail: ______________________________________________________ Expert AutoStats® 4N6XPRT BioMeknx™ Expert Qwic Calcs® 4N6XPRT Ped & Bike Calcs® 4N6XPRT StifCalcs® Expert VIN DeCoder® (pkg) Expert TireStuf® Order Processing

- $ 675.00 ea.

- $ 550.00 ea.

- $ 275.00 ea.

- $ 375.00 ea.

- $ 700.00 ea.

- $ 575.00 ea.

- $ 85.00 ea.

= ________ = ________ = ________ = ________ = ________ = ________ = ________

- Check = $5.00 / Credit Card = $10.00 / Govt. P.O. = $15.00 = _______ Notarized Affidavit Requirement $25.00 per required Notarized Signature = _______

Q Deliver via electronic download (Email address Required) Q Ship on USB - $50.00 per disk per program California Sales Tax

- 8.50%

TOTAL (U.S. Dollars)

= 0.00 = ______

= ________

= ________

Search for vehicles by entering Year, Make, and Model, or by any combination of: Length, Wheelbase, Weight, Body Style, Make, Model, and Impact location

Enclosed is:

Print out data and stiffness for single tests, or a Test Summary Stiffness Report when more than one test meets your search criteria

Card Number: _______________________________________________ Name on Card: _______________________________________________ Signature: ________________________________________________

For more information, program order form, and sample printouts please visit our web site at http://www.4n6xprt.com. You may also call us at (619) 464-3478 M-F, 9a-5p (PST), if you have specific questions.

www.4n6xprt.com/4n6sc.htm

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Visa ___ MasterCard ___ Am. Ex. ___ Exp ____/____ - Check ___ - Gvt PO ___

Please Make Checks*/Purchase Orders Payable to:

4N6XPRT Systems®

8387 University Ave - La Mesa, CA 91942-9342 - U.S.A. FAX: (619) 464-2206 Phone: (619) 464-3478 Web: http://www.4n6xprt.com Checks *MUST* be drawn on a U.S. bank. Orders are shipped within 10 working days of receipt.

Prices subject to change without notice.

Multiple orders and Package discounts available. Please call for details.

5/18/2022 9:05:20 AM

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