Volume 15, Issue 2 by Collision Publishing

ollision C

Volume 15 Issue 2

The International Compendium for Crash Research

Using Civil Twilight Envelopes

To describe commercial trucks’ headlamp illumination

Crashology: Getting It Right

Analysis of a real-world crash with Toyota EDR data, Toyota vehicle control history, and PCS images

Did You Find Any Errors

When you read through the data?

Electric Scooter

Hard brake, acceleration, and top speed testing

3D Delta-V

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Contents

Volume 15 Issue 2

inside 4

Letter from the Editor

Collision Magazine Info and Advertiser Index

features 28

Using Civil Twilight Envelopes to Describe Commercial Trucks’ Headlamp Illumination by Jeffrey Andre, April Yergin and Allen Vaughan

Drag Sled Mechanics: Fundamental Theory and Experimental Verification by Frank Navin,

Crashology: Getting It Right: Analysis of a Real-Word Crash with Toyota EDR Data, Toyota Vehicle Control History, and PCS Images by Wesley Vandiver and Robert Anderson

3D Delta-V

Toyota Vehicle Control History: "Sudden Braking History” Recording Characteristics

by Micky Marine 78

by Joseph Teitelman, Eric Rodos, Daniel Wolfe and Michael Helker

Electric Scooter Hard Brake, Acceleration and Top Speed Testing by Robert D Anderson, Michael Rosenfield and Russell Anderson

case study 6

Case Study: "Did you find any errors in the data as you read through the data?" by W. R. Rusty Haight and David W. Sersen

Case Study Solution: "The effect of non-planar acceleration captured at the Airbag Control Module on the recorded EDR delta-V data" by W. R. Rusty Haight and David W. Sersen www.collisionmagazine.com

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PR OB LE M:

CA SE

"Did you find any errors in the data as you read through the data?" W. R. Rusty Haight

Collision Safety Institute

David W. Sersen New York State Police

magine a crash being investigated just a few short years ago, easily within the span of most of our careers, where we were happy – perhaps even excited – to get Event Data Recorder (EDR) data from just one of the involved vehicles. We were all the more excited when it

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had more than "just delta-V" data, when it also included Pre-Crash data! In those early days, finding more than one involved vehicle with accessible EDR data which included Pre-Crash data was like finding the pot of gold at the end of the proverbial rainbow. Today, it becomes increasingly

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likely that we'll find that "pot of gold" data set more often as the majority of light trucks, passenger car and SUVs have not only accessible EDR data, but that data has become far more element rich and detailed. But has it made effectively applying the data really any easier? This issue's Case Problem comes from a real-world crash, captured in part on video, where both of the involved vehicles have similar, nearly identical data sets. Both are General Motors (GM) vehicles, both are "49CFR563 compliant"1 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 – the 2013 Buick LaCrosse (Allure) – has what is identified as an "SDM10Pconti" airbag control module (ACM). The other involved

vehicle, a 2017 Chevy Tahoe, has an ACM identified as a "SDM30-delphi." But it is, in part, some of the similarities found in the data that becomes the basis of this Case Problem. Background To "set the stage," the police are chasing a Buick LaCrosse. The why and where isn't terribly important to the Case Problem, in fact, for the Case Problem at hand, that it was a pursuit isn't all that critical except that the other involved vehicle is, as the astute reader might now expect, a police Chevy Tahoe. At a point just before the crash, the deputy driving the Tahoe is aware that the pursuit of the LaCrosse is coming at him, heading his way. He approaches an intersection where he knows the fleeing LaCrosse could make what would be, for the fleeing driver, a left turn or he could go straight, continuing opposite the direction the Tahoe would be then approaching that intersection.

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Using Civil Twilight Envelopes to Describe Commercial Trucks’ Headlamp Illumination Jeffrey Andre, PhD Department of Psychology, James Madison University, Harrisonburg, VA Contrast Associates, LLC, Moseley, VA

April Yergin, BS Allen Vaughan, BS ATA Associates, Inc., Houston, TX

bstract The present study quantified headlamp illumination from commercial trucks using the civil twilight envelope methodology (Andre & Owens, 2001). This approach uses visual performance data during civil twilight’s illumination levels to provide an easily understood description of useful headlamp illumination. Our goal was to provide truck drivers with information concerning the usefulness of their headlamps. We used the dark limit of civil twilight as our demarcation of farthest distance receiving useful illumination. Illumination measurements from four new commercial trucks were collected at night using a procedure similar to Andre and Owens. We found civil twilight distances similar to those found previously in passenger vehicles. Along the vehicle’s midline, the average civil twilight distance was 221.4 ft with low beams and 571.9 ft with high beams. There was also a substantial amount of variability among measurement locations for both beam intensities. Pursuant to our study’s goal, we report information that could educate drivers about their headlamp systems’ capabilities and limitations as defined by human visual performance in low light conditions.

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Introduction While the human visual system functions over a wide range of illumination, light levels present during civil twilight define a vital transition time when visual capabilities to identify unmarked, unlit objects become severely degraded. In 2001, Andre and Owens described vehicle headlamp illumination in terms of a “civil twilight envelope” to estimate the extent of useful illumination in front of a vehicle. Given that there are approximately 2.9 million tractor-trailers on United States roads (US Department of Transportation; 2017 data), the present study measured the headlamp illumination of commercial tractor-trailers using the civil twilight envelope methodology in an attempt to quantify the extent of useful illumination in front of such vehicles. Importantly, the goal of our study was not to compare or differentiate among truck manufacturers, but rather to provide a market-weighted analysis of the current fleet. This paper will first introduce existing headlamp regulations. Next, we will briefly explain the two-visual systems hypothesis before discussing what civil twilight is and why its illumination levels are important to understanding human visual performance. Finally, a review of the Andre and Owens (2001) research will precede a discussion of the current study's rationale, experimental methodology, findings, and discussion.

of their vehicle’s lighting systems when driving at night. Indeed, the regulations discuss neither headlamp throw distance nor relevance to drivers’ visual performance. Headlamp lighting information should be provided in an easily understood format based on the human visual system and described in common roadway parameters. The Two Visual Systems The human visual system has evolved for both bright and dark conditions, although our “night” vision is not nearly as capable. During the daytime, visual performance is determined mostly by cone photoreceptors’ functioning in and around the eye’s fovea located in the central retina. The cones help us see fine details (visual acuity), varying brightness levels (contrast sensitivity), an object’s colors and movement. Cones are not as sensitive to light as their counterpart rod photoreceptors, because they function primarily in bright conditions when there is an abundance of light to capture. Rods, conversely, are extremely sensitive to light since they mostly operate in low light or nighttime conditions. Rods detect brightness differences but do not “see” color, nor is their acuity typically adequate for object identification.

The day-night distinction between photoreceptors is one physiological basis for the two-visual systems hypothesis. The theory’s premise is the physiological existence of sepaExisting Headlamp Regulations rate cortical streams of processing of “what” an object is versus “where” it is (or “how” to The lengthy Code of Federal Regulations interact with it). Some of the earliest work (§571.108) that discusses headlamps also in- on this can be traced back to the late 1960s cludes information on other reflective devices when a quartet of researchers published their found on both the front and rear of vehicles research on mammals and fish that suggested including commercial tractor trailers, school the dichotomy (see Held, 1968; Ingle, 1967; busses, and motorcycles. The headlamp sec- Schneider, 1967; Trevarthen, 1968). Trevartions of the code discuss headlamp types, then later named the “what” pathway focal vimounting positions, aiming procedures/ sion, and it consists of our ability to discrimimechanisms, replacement bulb information, nate patterns, colors, and object recognition and beam photometric requirements. These (see, e.g., Owens, 2003). It uses mainly the beam requirements are discussed in terms of central retina and fovea. minimum and maximum photometric intensity values (in candelas) which are broken Conversely, the “where” or ambient pathway down by different test point locations (in de- consists of postural control, orientation, and grees). Unfortunately, these codes are practi- visual guidance activities and utilizes more of cally useless to drivers who are interested in the peripheral retina. Factors that differenunderstanding the capabilities and limitations tiate the two systems include low light (diswww.collisionmagazine.com

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systems hypothesis. Perception & Psychophysics, 68(3), 353-361. Francis, E. L, Tyrrell, R. A. & Owens, D. A. (2020). Perception response time and its misapplication: a historical and forensic perspective. Theoretical Issues in Ergonomics Science, 21(3), 327-346. Held, R. (1968). Dissociation of visual functions by deprivation and rearrangement. Psychologische Forschung, 31, 338-348. Ingle, D. (1967). Two visual mechanisms underlying the behavior of fish. Psychologische Forschung, 31, 44-51. Leibowitz, H. W. & Owens. D. A. (1977). Nighttime driving accidents and selective visual degradation. Science, 197, 422-423. Leibowitz, H. W. & Owens, D. A. (1991). Can normal outdoor activities be carried out in civil twilight? Applied Optics, 30, 3501-3503. Leibowitz, H. W., Owens, D. A. & Post, R. B. (1982). Nighttime driving and visual degradation (Society of Automotive Engineers Technical Paper Series No. 820414). Warrendale, PA: Society of Automotive Engineers. Leibowitz, H. W., Owens, D. A. & Tyrrell, R. A. (1998). The assured clear distance ahead rule: Implications for nighttime traffic safety and the law. Accident Analysis and Prevention, 30, 93-99. Owens, D. A. (1999, January). The twilight concept vs. a computer model: Alternate approaches to understanding visibility. Paper presented at the 78th Annual Meeting of the Transportation Research Board, Washington, DC. Owens, D. A. (2003). Twilight vision and road safety: Seeing more than we notice but less than we think. In J. Andre, D. A. Owens & L. O. Harvey, Jr. (Eds.), Visual Perception: The Influence of H. W. Leibowitz (pp. 69-79). Washington, DC: American Psychological Association. Owens, D. A. & Andre, J. T. (1996). Selective visual degradation and the older driver. IATSS Research, 20, 57-66. Owens, D. A., Francis, E. L. & Leibowitz, H. W. (1989). Visibility distance with headlights: A functional approach (Society of Automotive Engineers Technical Paper Series No. 890684). Society of Automotive Engineers. Warrendale, PA. Owens, D. A. & Tyrrell, R. A. (1999). Effects of luminance, blur, and age on nighttime visual guidance: A test of the selective degradation hypothesis. Journal of Experimental Psychology: Applied, 5(2), 115-128.

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Schneider, G. E. (1967). Contrasting visuomotor functions of tectum and cortex in the golden hamster. Psychologische Forschung, 31, 52-62. Sivak, M., Flannagan, M., Kojima, S., & Traube, E. C. (1997). A market-weighted description of low-beam headlighting patterns in the U.S. (Tech. Report No. UMTRI-97-37). Ann Arbor: University of Michigan Transportation Research Institute. Sivak, M., Helmers, G., Owens, D. A., & Flannagan, M. (1992) Evaluation of proposed low-beam headlighting patterns. Report No. UMTRI-92-14. University of Michigan Transportation Research Institute: Ann Arbor. Trevarthen, C. B. (1968). Two mechanisms of vision in primates. Psychologische Forschung, 31, 299-337. Acknowledgments We would like to thank the following individuals for invaluable help on this project: Dale Runkle (CDL driver), Martin Garsee (Facilities Operations Manager, Houston Community College), and Robert Swint (CEO, ATA Associates, Inc.). We are incredibly grateful to International Trucks of Houston, Rush Truck Center of Houston, Vanguard Truck Center of Houston, and Houston Freightliner & Western Star. We would also like to thank Thomas Bohan and Richard Tyrrell for their helpful suggestions on earlier versions of the manuscript. Author Bios Jeffrey Andre earned his Ph.D. in experimental psychology (visual perception) in 1995 from The Pennsylvania State University. He is currently a Professor of Psychology at James Madison University, Harrisonburg, VA. He is also the sole proprietor of Contrast Associates, LLC, a visual perception/human factors consulting firm based in Moseley, VA. April Yergin earned her B.S. in Aeronautical Engineering Technology in 1986 from Arizona State University and an ACTAR certification in 1997. She is currently a senior accident reconstructionist and analyst at ATA Associates, Inc. in Houston, TX, working frequently on heavy truck accidents. Allen Vaughan earned his B.S. degree in Mechanical Engineering from Wright State University. He is currently a staff engineer at ATA Associates, Inc. in Houston, TX. He is also an accident reconstructionist who works frequently in automobile accidents, including heavy truck and conspicuity related accidents.

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

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The Crash Hub Expert Directory The Crash Hub is a specialized expert directory for crash reconstructionists and traffic investigators. This directory allows the user the ability to search, review, and retain vehicle crash experts around the world. Our directory creates hundreds of leads for new cases! The Crash Hub is also much more than an expert directory site because each member of The Crash Hub has the ability to add meaningful content to the site in the form of articles, events, training classes, photo albums, and videos. The Crash Hub can also be used as job search site and a classified ads directory.

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_____Drag_Sled_Mechanics:_ Fundamental Theory and Experimental Verification Frank Navin, Ph.D., D.Sc (Hon), Professor Emeritus, University of British Columbia

ntroduction Measuring a tire-pavement’s coefficient of friction is simple in theory but very complex in practice. Major studies have concentrated on wet pavements that usually present the most difficult driving conditions. Studies by Wambolt et al (1995) and a New Zealand study by Wilson and Black (2009) illustrated the complexity of friction measurements on wet highway pavements. The problem is about as difficult on dry pavements. Some of the easily measured factors to be considered are shown by bold type in Figure 1. The details will be presented in the next section. This paper will concentrate on the needs of collision reconstruction measurements on dry asphalt pavements.

stitutions and funding agencies. See Appendix A for the participants in this research.

There was a time during the late 1990s and into the 2000s when the collision reconstruction community was embroiled in the “drag sled wars”. Those questioning the drag sled included Bartlett, Baxter, Liversay, Standard and Wright (2006). Supporters included Calhoun, Dinitto, Biller, Cumming and Osterhoult (2010) and Navin and Musa (2004). Recently a paper by Navin (2019) gave a better definition of drag sled mechanics. The dispute continues to stimulate debate in professional circles and various courts of law.

Using a drag sled during collision reconstruction requires the consideration of two independent systems. First is the drag sled and the second is the braking (skidding) vehicle. The following outlines the nature of the two systems.

This research represents over 20 years of periodic effort by the author and about 40 other professional reconstructionists. Funding and in-kind support was roughly $150,000 CDN provided by a number of in-

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The experiments reported here started in about 2002. Aim The main purpose of this paper is to present a theoretical and empirical relationship between a drag sled’s; weight, pulling force, and pull angle; the definition of coefficient of friction and the drag factor. Another aim is to illustrate that a drag sled, properly used, is an acceptable device to measure a drag sled’s coefficient of tire-pavement friction. Study Method

Drag Sled Experiments Prior to the author’s drag sled study, vehicle skidding was mainly for police purposes to “calibrate” drag sleds. There was a major push at WREX2000 that demonstrated that “pullers” had to be trained to successfully use a drag sled. In the early 2000s, the author organized a Latin Square experiment carried out by well-trained Royal Canadian Mounted Police (RCMP) collision reconstructionists. The results were reported in Navin et al

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2009 at IPTM. The main result was the recognition that a manufactured drag sled could reduce much of the variance observed between drag sleds and users.

The information in Figure 1 was used to minimize the number of factors for the vehicle skidding experiments. The following were the factors:

A recent theoretical analysis of the drag sled used the “classical point mass system” to derive a general equation. The equation includes the pulling force, the drag sled weight, pull angle and the definitions of coefficient of friction and drag factor. The equation defines the relationship of the drag factor to the pull angle and the coefficient of friction for any pavement. The details will be presented in a later section.

1. Vehicle mass, measured as load per tire;

Vehicle Experiments Based on extensive research of the scientific and collision reconstruction literature and limited observations for police skidding tests, the author hypothesized that there was some relationship between a vehicle’s deceleration rate and tire load and speed. At the time, during the early 1980s, the cost of suitable research accelerometers was prohibitive. The simple mechanical and visual observations were not adequate to make the required measurements. The G-analyst (1980) changed the experimental procedure by providing a reasonably priced accelerometer but it had limited data collection. An early study by Reed and Kelsin (1987) gave accelerometer results from emergency braking. Another example is the experiment by Eubanks et al (1993) of vehicle skidding on a concrete runway. It gave detailed and redundant skidding distances and accelerations for the same vehicle. Other studies by Ruller (1993) in Australia for asphalt gave results of similar precision. An excellent study by Heinrichs, et al (2004), illustrates the instrumentation needed for a truly scientific experiment. The availability of the Vericom family of accelerometers dramatically changed how police braking experiments were undertaken and the precision of the results. The data collected included time, distance, speed, and acceleration. Reconstructionists could now look at the details of the braking during the entire process. In early 2000s, the author was asked by IPTM to study the relationship between a skidding vehicle and a drag sled. Based on previous research, it was decided to do a detailed study of braking (skidding) vehicles that were equipped with redundant measuring devices when possible.

2. Speed at the start of visible skid marks; 3. Asphalt pavements that were; clean, level, dry and worn or weathered; 4. Vehicles that were well maintained and had good tires; 5. Drivers that were usually police trained and familiar with emergency braking; 6. Vehicles equipped with accelerometers or a 5th wheel to measure deceleration and time; 7. Visible skid marks that were measured by competent police trained reconstructionists; and 8. Experiments that were conducted during the summer under reasonable weather conditions. Additional measurements of temperature of the tire patch and asphalt were taken but abandoned due to inconsistencies of measurements. Other standard police measuring devices such as shot markers were also used but unfortunately not consistently. Referring back to Figure 1, it is easily seen that the experiments did not include all possible factors but an attempt was made to have reasonably reproducible experimental results that were easily measured or observed. Results Drag Sled’s Theoretical Relationship The forces acting upon a sliding body on a firm surface is shown in Figure 2. There are three forces in this case; the weight acting down, the pulling force acting at angle θ and the resultant resisting motion. In this particular case, they all act through a single concurrent point on the surface of the pavement-tire interface. The coefficient of friction on a firm surface is defined as the force resisting motion (F) divided by the normal force (N), see Figure 2. Mathematically the equation is:

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APPENDIX B, continued DATA FOR VEHICLE BRAKING ON WORN OR WEATHERED ASPHALT VEHICLE BRAKING EXPERIMENTS ON WORN OR WEATHERED ASPHALT Tire Load Speed at Start of, mph Distance, ft f(v,s) f(v,sb) Location Device 1000lb/tire Braking Skidding Skidding Braking

1.26 1 1 0.806 Florida FHP Outside Parking 1.26 1 1 0.838 Lot 1.26 1 1 0.842 iLoad Pro Digital 1.26 1 1 0.875 Crown Victoria 1.26 1 1 0.861 June 2009 1.26 1 1 0.868 1.30 22.5 16.9 12.0 23.1 0.785 0.770 Prince George, BC RCMP vehicle 1.30 23.2 19.6 16.1 23.1 0.788 0.778 VC3000 1.30 24.2 20.0 16.7 26.5 0.790 0.778 Radar 1.30 24.3 20.8 18.4 na 0.779 0.768 + Shot Marker 1.30 25.1 21.7 19.4 29.3 0.800 0.772 Crown Victoria 1.30 41.4 38.2 64.8 80.3 0.734 0.737 2004 1.30 41.9 38.0 64.8 na 0.736 0.741 August 2008 1.30 44.9 40.1 72.5 92.1 0.733 0.734 1.30 47.4 41.7 77.1 105.1 0.745 0.727 1.30 56.6 48.4 109.1 154.2 0.708 0.733 1.30 57.5 56.3 151.8 174.6 0.688 0.683 1.30 59.9 55.6 139.2 163.4 0.734 0.744 1.30 1 0.68 Prince George, BC Smooth Concrete 1.30 20.3 18.0 17.8 27.7 0.600 0.670 Same as above 1.3 21.3 19.0 16.8 27.5 0.708 0.724 1.30 21.5 19.0 20.9 31.2 0.571 0.626 1.30 21.9 18.7 16.9 29.4 0.681 0.708 PG, Prince George parking lot; CA parking lot;. PTC Pacific Training Center track

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

Robert Anderson

Collision Forensics, Inc.

Biomechanics Analysis

Getting It Right: Analysis of a Real-Word Crash with Toyota EDR Data, Toyota Vehicle Control History, and PCS Images

rash reconstructionists are regularly tasked with forming opinions regarding fault and/or causation with less-than-complete information and/or evidence. The responsibility lies with the investigator to collect as much evidence as possible so that responsible conclusions can be reached. Many competing interests can interfere with an investigator’s efforts to be thorough in gathering evidence – time limitations, complexity of retrieval, management directives, case load, etc. To that end, the investigation of an incident in which partial evidence is obtained could lead to conclusions that would be changed given one more item of evidence.

both involved vehicles were disabled and police photographs were not taken. Shown in Figure 1 is the officer’s diagram depicting a right rear contact with the Chevrolet and left front and left rear contacts with the median wall. Roadway evidence such as debris or tire marks were not identified. In Figure 1, Vehicle 1 is the Lexus and Vehicle 2 is the Chevrolet. The Chevrolet driver told the investigating officer that she was in the number three lane when the Lexus began merging into her lane and side-swiped her vehicle.

The case being discussed in this feature is an example of a crash analysis that demonstrates how vehicle damage, event data recorder evidence and Toyota vehicle control history were used collectively to solve a crash scenario with inaccurate witness statements and limited scene evidence.

The Lexus driver told the investigating officer that he was in the number three lane when he was hit and spun into the center median wall. In follow up at the hospital, the officer stated that the Chevrolet driver claimed that the Lexus suddenly changed lanes, which caused the Chevrolet to rear-end the Lexus. The Lexus driver reiterated that he was not changing lanes, but rather he was just driving in the number three lane when they rear-ended.

The general scenario of the case starts with the fact that visiting grandparents were loaned their daughter’s 2021 Lexus RX350, to drive during their stay. That vehicle was involved in a collision in Arizona that was investigated by law enforcement.

A witness told the investigating officer that she was right behind the vehicles and saw it all happen. The Lexus was in the number two lane and began to merge into the number three lane without a blinker and into the Chevrolet.

According to the police report, at about 10 PM, the Lexus and a 2015 Chevrolet Camaro were traveling southbound on the State Route 51 in Phoenix, Arizona. It was dark with streetlights, the weather was clear, the roadway was dry and level. At the scene of the collision, the highway curved left and no unusual roadway conditions were noted. The posted speed limit was 65 mph. As a result of the collision,

With an independent witness corroborating the Chevrolet driver’s version of the events, the investigating officer concluded that the Lexus failed to maintain its lane and merged from the number two lane into the Chevrolet, as depicted in the officer’s diagram. This caused the Lexus to lose control, spinout and collide with the center median wall. The officer’s estimated speed for both vehicles was 65 mph.

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Figure 1: The officer’s diagram

Figure 2: The Arizona DOT (ADOT) traffic cam image of the crash scene www.collisionmagazine.com

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3D DELTA-V MICKY MARINE SSI PHOENIX, INC.

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n this article the equations necessary to calculate delta-V in three dimensions using crash test accelerometer and angular rate data are developed. This is an expansion of the development presented in reference [1] which was focused on the yaw-plane. An expansion to three dimensions requires care be taken in the instrumentation setup of the crash test vehicle and an understanding of the effects of gravity on accelerometers that undergo general rotational motion. An additional consideration is that of describing vehicle orientation. In full-scale automobile crash testing, angular rate sensors are often used to measure test vehicle angular velocity. Typically, these sensors are oriented such that the angular rates about the vehicle longitudinal, lateral and vertical axes (p, q, and r as shown in Figure 1 [2]) are measured. However, a set of three angular position parameters that define the orientation of a body and whose time derivatives are also uniquely p, q, and r, respectively, does not exist [3]. Accordingly, the orientation time-history of the vehicle cannot be determined through direct integration of angular rate sensor data.

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Figure 1: SAE vehicle coordinate system [image from SAE J670e, 1976]. To assist in the endeavor of establishing a vehicle orientation time-history, a set of parameters known as Euler angles are used. There are several different sets of Euler angles that one can employ for a motion analysis; the set used herein is often used in aeronautical engineering and comprises the heading angle (ψ), attitude angle (θ), and roll (or bank) angle (φ). To visualize the orientation of a body relative to a space-fixed system (X, Y, and Z axes), the rotations take place conceptually in the listed order (ψ,θ,φ). Referring to Figure 2, the first rotational displacement (heading angle ψ) is about the Z axis and establishes an x'-y'-z' orientation. The second rotational displacement (attitude angle θ) is about the y' axis and establishes an x"-y"-z" orientation. The final rotational displacement (roll angle φ) is First rotation (T1):

about the x" axis to establish the final x-y-z vehicle orientation. The transformation matrix for each rotation is provided below. Note that “S” and “C” represent the sine and cosine, respectively, of a given angle. Using the above transformations and the proper substitutions, the transformation from a space-fixed coordinate system to a vehicle-fixed coordinate system is then found to be:

Second rotation (T2):

Third rotation (T3):

Figure 2: Euler angle progression

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Toyota Vehicle Control History: "Sudden Braking History” Recording Characteristics Joseph Teitelman, Eric Rodos, Daniel Wolfe, & Michael Helker ARCCA Inc.

ntroduction With the recent introduction of vehicle control history (VCH), Toyota has ushered in a new frontier in advanced vehicle data which leverages the ever increasing amount of technology contained within modern vehicles. First adopted in 2013, Toyota VCH is a new data recording functionality which records and stores information relating to a variety of non-collision dependent triggers. Vehicle control history triggers include specified driver behaviors, the activations of numerous vehicle systems, and occurrences related to advanced driver assistance systems (ADAS). Toyota VCH expands upon both the range of incidents where collision investigators and reconstructions may expect stored data, and the amount of data which is stored relating to those incidents. Toyota VCH records are generally recorded over a longer period of time and at an equal or higher frequency than traditional event data recorder (EDR) data and can even include the date/time from the vehicle’s clock and photographs from the vehicle’s forward facing camera.

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Starting in the model year 2000, Toyota began equipping its vehicles with event data recorders, which record and store information related to qualifying collision events. Pre-crash data elements from sensors and systems located across the vehicle were introduced in Toyota EDRs shortly thereafter. Modern Toyota EDRs contain data parameters which extend beyond the data elements prescribed by 49CFR563, which Toyota considers as only minimum requirements. [1] Previous research has been published which has focused on the accuracy of the data recorded across various generations of Toyota EDRs. [2] This research, and the general acceptance of event data throughout the accident reconstruction community has resulted in the establishment of Toyota EDR data as a critical tool to collision reconstructionists. Much like EDR events, Toyota VCH records are recorded utilizing various sensors and vehicle systems and are stored in non-volatile memory within the airbag control module. However, it should be noted that vehicle control history is located in separate memory areas from EDR data and that the imaging procedure differs between the two data recording functionalities. Despite the accuracy of vehicle control history data being tied to that of Toyota EDR, prior research has been conducted which specifically validates the accuracy of vehicle control history data. These studies, which evaluated various VCH data elements against reference instrumentation, have shown accuracy which is comparable to that of EDR data. [3,4] Vehicle control history data provides tremendous utility to collision reconstructionists. By storing data relating to a collection of non-collision dependent triggers, critical information is now often accessible regarding incidents that are not traditionally recorded by EDRs including near-impacts and low-severity impacts such as those involving pedestrians, cyclists, and animals. Based on field investigations conducted by these authors, and on published literature on Toyota VCH, [5] it is clear that the “sudden braking history” trigger has a particularly high propensity to record as a result of, or in the moments preceding a collision event. For models equipped with Toyota Safety Sense 2.0 or newer, photographs from the forward facing camera are recorded and stored along with the data for each “sudden braking history” trigger. [6] The “sudden braking history” trigger shares a memory recording area with the similarly named “sudden turning history”. The prevalence of “sudden turning history”

has been shown to be much less than “sudden braking history”, however, the data is equally valuable when available. As the circumstances which result in the recording of these triggers often occur prior to a collision, the recorded data regularly overlaps with the 5 seconds of pre-crash data which is recorded by the EDR. For these reasons, this research will focus on the “sudden braking history” and “sudden turning history” triggers. Since 2012, automobile manufactures have had regulatory guidance provided by 49CFR563 regarding event data recorder trigger thresholds. There has been considerable research conducted within the accident reconstruction community which has aimed to investigate and characterize the actual recording behavior of various event data recorders. Unlike with EDRs, there is no existing guidance or accepted benchmark at this time to follow regarding the trigger thresholds for non-collision dependent data such as Toyota VCH. Many vehicle control history events have clear triggering parameters such as any recorded activation of the antilock-brake, traction control, or stability control systems. However, the sudden braking/turning history triggers have more abstract labels which do not provide a clear understanding of their recording behaviors. In a publication by Toyota, [7] it was referenced that the parameter which triggered the recording of “sudden braking history” was Gx, or longitudinal acceleration, however, a specific threshold was not mentioned and an example dataset was not provided. In said publication, no mention of the “sudden turning history” trigger was made. It is critical to the accident reconstruction community to understand when, and why electronic vehicle data is recorded. This research aims to investigate which parameters trigger the recording of the “sudden braking history” and “sudden turning history” records within Toyota vehicle control history, and to identify their trigger thresholds. Additionally, the collected data will be analyzed and recording characteristics and trends which appear within the information will be explored. Methodology For this study, vehicle control history data was downloaded from 19 Toyota/Lexus vehicles in order to acquire and analyze naturalistic occurrences of the “sudden braking history” and “sudden turning history” triggers. The involved vehicles, detailed in Table 1, were comprised of 10 different models including se-

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Electric Scooter Hard Brake, Acceleration and Top Speed Testing Robert D Anderson Biomechanics Analysis

Michael Rosenfield RSR Engineering

Russell Anderson

Collision Analysis & Research

ntroduction Recently, the popularity of e-scooters has mushroomed. These electric vehicles are inexpensive, fun to ride, they may not require a license or insurance and they are thought to be an eco-friendly choice. Sharable e-scooters can be rented with an app, then left at the destination for the next customer that comes along. Many cities have started pilot programs to test the viability of e-scooters as a mobility option.[1,2,3,4] They are popular around college campuses, beaches, urban areas, etc. With their rise in popularity, there has been a commensurate rise in crashes and injuries.[5,6,7,8,9]

suggested although it was acknowledged that a 2017-18 UCLA study found that most e-scooter riders did not wear a helmet and that 40 percent of the injuries observed in the study were head injuries.[7] BBC reports that while escooters offer a seemingly fun and environmentally friendly option for short journeys, a range of questions about their safety and sustainability have emerged in the previous two years. Although shared models are emission free at the point of use, manufacturing, moving and redistributing them results in greenhouse emissions. On pathways and sidewalks, e-scooters pose dangers to pedestrians and wheelchair users, and particularly to people with visual impairment, but using scooters on roads without sufficient infrastructure such as cycle lanes is also risky. [8] Todd et al. conducted an observational study of e-scooter rider behavior in west Los Angeles. It was noted that there was a potential for e-scooter operators to accelerate to the 15 mph maximum speed allowable in California sooner than a bicycle or traditional kick scooter. It was found that the proportion of helmet users on e-scooters was much less than that of bi-

Consumer Reports found that most of the e-scooters they tested had a top speed of 15 mph on flat pavement. It was concluded that if used safely, e-scooters can be a viable - not to mention quick, portable, fun - way to fill transportation gaps. Helmet and possibly pads and guards were

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Figure 1: Still frame from SATAI 2020 Number 1 Conference Crash Video cyclists. In fact, nearly 90 percent of e-scooter riders did not wear a helmet. Operators were demonstrated to be more relaxed about complying with vehicle codes as demonstrated by the greater likelihood of travel in the opposite direction of traffic and on sidewalks. [10]

their testing, compared to riders in the 115 to 150 pound range, lower acceleration and braking performance was observed for a 274 pound rider. It was reported that the share application might have a ride history or summary for the rental, although this had not yet been explored.

Scooter crashes have also become part of crash test demonstrations. For example, at the 2020 SATAI Crash Conference, the crash program led with two automobile-toscooter crash demonstrations, one of which is shown in Figure 1. During the conference, Accident Science, Inc. presented the results of yet-to-be-published instrumented e-scooter acceleration and hard brake testing. [11] In

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CA SE SO P LU RO TI BL ON EM :

"The effect of nonplanar acceleration captured at the Airbag Control Module on the recorded EDR delta-V data"

W. R. Rusty Haight

Collision Safety Institute

David W. Sersen New York State Police

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To review… The police are chasing a Buick LaCrosse. As pointed out, the why and where isn't terribly important to the case problem, in fact, for the case problem at hand, that it was a pursuit isn't all that critical except that the other involved vehicle is a police Chevy Tahoe. At a point just before the crash, the deputy driving the Tahoe is aware that the pursuit of the LaCrosse is coming at him, heading his way. He approaches an intersection where he knows the fleeing LaCrosse could make what would be, for the fleeing driver, a left turn or he could go straight, continuing opposite the direction the Tahoe would then have just been ap-

proaching that intersection. Frame captures from a nearby gas station security camera are offered in the Case Problem statement found earlier in this issue as well as photos of the scene and involved vehicles and applicable portions of the EDR data translation reports created with the latest version of the Bosch CDR Tool software at the time this issue of Collision is published. The deputy in the Tahoe pulls up to the intersection slowing as the pursuit approaches in the distance. In the Tahoe's Pre-Crash Data table, we see that, during the last 5 seconds leading up to the crash, the deputy slows through 7mph (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: the being last pre-crash sample before "algorithm enable." After the Tahoe has been fully stopped for about 3 seconds, there's a pretty spectacular crash. For reasons beyond the scope of this case problem, the fleeing driver elected to drive the LaCrosse over the centerline in the road and engage the Tahoe fully head on; "hood ornament-to-hood ornament" as it were. Although the cars were actually weighed after the crash, without occupants and not including parts which were no longer with the vehicles, given that the published weights varied so much from that found for the subject vehicles we have adopted – for this Case Problem – the average weights for the involved vehicles. For the Case Problem, the weight range for the LaCrosse as previously describes was 3550 to 3835 lbs (16101739 kg), the applied average of the high- and low-end weights for the solution discussion is adopted as 3693lbs (1675 kg). For the Case Problem, the weight range for the Tahoe as previously described was 5550 to 5683 lbs (2517-2577 kg), the applied average for the solution discussion is adopted as 5608 lbs (2544 kg). The reader is welcome to adjust the weights as they feel is appropriate.

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