2015 CDR SUMMIT DVD
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2015 Vol.10 Iss.1
ollision C The International Compendium for Crash Research
Volume 10 Issue 1
Collision: The International Compendium for Crash Research Volume 10, Issue 1 - SPRING 2015
collisionmagazine.com
Spring 2015
Contents
Spring 2015
Volume 10 Issue 1
inside 4
Letter From the Editor
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Letter From NAPARS & Industry Partners
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features 8
Data Mining the NHTSA NASS CDR Database by: Tobias Achstetter, Fabian Kübler, Michael Wolf and Sean Haight
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The implications of the CRASH3 uniaxial structural response model and the nature of available collision test data in regards to work-energy relationships for oblique impacts by: Jai Singh
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Errors and Uncertainty in Deriving Speed Estimates from Skid Tests Taken at Accident Scenes by: William C. Fischer
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My Turn At the Wheel: A DIRTY TRICK BY A LAW OF PHYSICS, OR WHAT? by: Erik Carlsson
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Analysis and Performance of a Booster Seated 6 Year Old HIII Anthropomorphic Test Device When Utilizing Seat Belt Cinching For Lap Slack Control by: Michael T. Vecchio
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A Method to Establish Delta-V and Collision Force in a Two-Vehicle Collinear Collision where Stiffness Data for One of the Vehicles is not Available by: Jai Singh
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Video-Based Accident Reconstruction of TransAsia Flight by: Adam Cybanski
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Case Study Case Study Solution www.collisionpublishing.com
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>> Data Mining
The NHTSA NASS CDR Database Tobias Achstetter, Fabian Kübler, Michael Wolf and Sean Haight Center For Collision Safety and Analysis George Mason University
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ntroduction Since 1979, the National Highway Traffic Safety Administration (NHTSA) has been implementing a nationwide crash data collection program called the National Automotive Sampling System (NASS). It is sponsored by the U.S. Department of Transportation and is operated by the National Center for Statistics and Analysis (NCSA). <<ref 1>> Since the mid 1980’s, NASS has been split into two distinct reporting systems: the General Estimates System (GES), and the Crashworthiness Data System (CDS). The GES collects data on a sample of all police reported accident reports, while the CDS collects additional detailed data on a smaller sample of accidents. For this research, the focus will be on the NASS CDS variant.
The data for the NASS CDS database is collected via 24 geographical locations which are called Primary Sampling Units (PSU). The collected data is then processed and sanitized to ensure privacy, then it is stored on the NHTSA website for analysis. The NHTSA website, which provides the ability to search the database, can be found at http://www.nhtsa.gov/NASS. The portal allows the user to search for specific cases, by vehicle, by accident type, damage, delta-v, etc. Once a case is selected, the user can view information about the accident such as: photographs, vehicle information, occupant information, injuries, scene diagrams, crush measurements, and more. In addition to the web portal, database software suites, like SAS, can also be used to interface with the NASS database.
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While most of this is known to the average safety researcher or crash reconstructionist, what is not typically known is that many of these cases also include Bosch Crash Data Retrieval (CDR) reports. Starting in sampling year 2000, NHTSA began providing PDF copies of the CDR reports from supported vehicles involved in NASS CDS accident cases. These files are located on the NHTSA website via file transfer protocol (FTP) at ftp://ftp.nhtsa.dot.gov/NASS/EDR_Reports/. Anyone with internet access can download packaged collections of CDR reports for a given sampling year. Each package contains all of the CDR generated reports for the specified year. Each file is organized by a reference number, which is also the filename. This filename includes the sampling year, the PSU, the case number, and the vehicle number. For example, on CDR report is named: 2000-12-193V1.PDF. Using the file name, the specific case contents, like photographs, can be accessed using the NHTSA NASS CDS webpage. From sampling year 2000-2012, there are approximately 7,450 CDR reports.
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otivation Currently, there is little to no research dedicated to the analysis of this large and valuable data set. The primary motivation of this research is to provide a roadmap for future research using the CDR data from the NASS CDS dataset. This research will outline one possible method for data extraction and organization, as well as some sample data mining techniques that can be used to extract meaningful data.
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Most of the analysis and research currently being done involving the NASS CDS is based on the data that is hardcoded by the NASS investigator. Due to incorrect/ incomplete information given to the investigator or human error, this objective method of analysis can be another piece of the puzzle for analysts. For example, there can sometimes be contradictory information between the NASS CDS data and the CDR report. For example, in case number 2001-45-064-V2, the police report indicates that the “belted driver and three nonbelted passengers of V2 were transported to the hospital …” However, the Bosch CDR file clearly states that the driver’s belt switch circuit status is listed as unbuckled. This information, which was passed to the NASS investigator via the police report does not match the data provided by the Event Data Recorder (EDR). While it is technically not conclusive either way (perhaps the driver was sitting on the buckled seatbelt in this case), using the CDR reports can shed some additional light on the NASS CDS case information.
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ethod for extracting data from CDR PDFs In order to make the data of the CDR PDF reports more accessible and to statistically examine the information that are provided in the CDR files, one goal of this research was to generate and populate a SQL database. The methodology that was used to achieve this goal is explained in some detail in the following paragraphs.
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DR Data Elements The first step was to select the data which should be extracted from the CDR PDFs. Figure 1 shows an example of an early 2000's General Motors CDR report file. On the left side, important parts of the PDF file are shown which holds the CDR file information such as Vehicle Identification Number (VIN), NASS Case Number (file name), the CDR software version number and the type of events recorded. For the system status at event, the authors extracted the seat belt status and the ignition cycle count. Similarly, crash parameters like vehicle speed, percent throttle and brake switch circuit status were extracted from the CDR reports.
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ata Extraction Schemes The database extraction scheme in Figure 2 was used to extract the data, shown in Figure 1, and to generate the database that can be used to propose scientific queries. The first step, was to convert the PDF to text files using a free Python module PDFminer <<ref 2>>, which is available for Python 2.7. Python 2.7 was the primary programming language used in this project. The most laborious part of the project was the several hundred lines of Python-code that were written to extract the data from the text files. To deal with the different types of CDR report formats, many
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Three car, in-line crash analysis with CDR Data Rusty Haight Collision Safety Institute
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or this case study, the Crash Analyst is presented with a case involving three cars; an otherwise “typical” in-line crash involving three vehicles. The involved vehicles are: a 2005 Ford 4wd F-150 SuperCrew (assumed weight is 5800lbs/2630kg), a 2010 Toyota Corolla (assumed weight 3000lbs/1361kg), and a 2007 Toyota RAV4 (assumed weight 3700lbs/1678kg). The Human Component The driver of the RAV4 said they were stopped in a line of traffic and heard tires skidding then felt an impact. The driver of the Corolla said they were in stop-and-go traffic behind the RAV4, at or near a stop when they heard skidding behind them then they were rearended and pushed into the RAV4. The driver of the F-150 said they thought the driver of the cars ahead braked unnecessarily. The Vehicle Component You may adopt that the RAV4 is in the “lead” position; numbered from rear-to-front in the group, the #3 vehicle. The Corolla is in the middle or #2 position and the F-150 is in the rearmost position in the line or the #1 vehicle. The damage to the involved vehicles can be seen in the photos accompanying this case problem. None of the vehicles had pre-existing damage in the areas involved in this event. All are seen in the accompanying photos at their controlled points of rest on the shoulder of the road post-impact having been moved there by the respective drivers. In terms of potential CDR Tool retrievable data, the truck is supported for PCM data but there was no deployment of airbags and one may adopt that, after the crash, the driver left the truck running so there would be no data remaining associated with this event. The RAV4 is supported for EDR/CDR data but is, for whatever reason, unavailable to the analyst for imaging. The remaining vehicle, the one in the middle of the three, is imaged and excerpts of the CDR report are provided in these pages of Collision for your review in this analysis. 20 Collision Magazine - Volume 10 Issue 1
The Environment Component The roadway in the area of this collision is a straight, relatively level 3 lane divided highway which was clear and dry at the time of the collision. The collision took place at approximately 9:00AM in the right-most travel lane for the direction all three had been moving and there was some stop-and-go traffic approaching an offramp about a quarter mile head of the area of impact(s). The Challenge: Given the available information, the CDR Data Analyst should be able to answer the following questions about this collision. No inference should be made from the order of the questions and, where appropriate, more than one value might be offered for a given question if the Analyst interprets that the question applies to, for example, multiple impacts. 1. What is the order of the impact(s)? Or, which vehicle hit which vehicle first? What information supports your conclusion(s)? 2. When the F-150 hits the Corolla, what is the closing speed of the F-150? 3. When the F-150 hits the Corolla, what is the speed of the Corolla? 4. When the F-150 hits the Corolla, what is the impact speed of the F-150? 5. What is the delta-V for the Corolla when it is hit by the F-150? 6. When the F-150 hits the Corolla, approximately how far is the Corolla away from (behind) the RAV4? 7. What is closing speed of the Corolla relative to the RAV4? Answers and a discussion are found later in this issue of Collision.
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Editor’s note: This case problem is drawn from an actual crash but where the vehicle history for the Toyota Corolla from which the CDR Data is drawn is known and documented. This is not drawn from a litigated case so this case problem is not a justification of an analysis, as is sometimes seen in published papers elsewhere. The CDR report offered for this case problem is displayed on these pages in the latest version of the CDR Tool software (version 16.0.1). Normally, of course, one would work from the CDR file but for this case problem so everyone reviewing it is on the same page, so to speak, the relevant pages of the report has been reproduced here and edited to efficiently fit the pages of Collision. For example, the data found on the page associated with “TRG 3” would normally span three pages in a CDR report but here have been condensed to one page making the delta-V graph smaller but allowing for normal print size on the remaining data elements. The hexadecimal data pages have been eliminated solely in favor of space considerations for this example. Since there is the possibility that a data element may be reported differently in a later version of the CDR Tool software, it is possible that there may be variations of this data, as represented, if translated with a future version of the CDR software, but, for this example, we will adopt it is the most current, accurate translation and reliable representation of the Data Limitations text we might work from. This case problem is offered as an example of how CDR data might be used in a crash where, for whatever reason, there’s just not a lot of other information to work with other than a few at-scene photos and the CDR report for one of the involved cars. Whether as a function of a limited amount of at-scene documentation or a designed case problem, this analysis relies on the information available and nothing more. Ideally, there might be more documentation such as crush measurements and perhaps even CDR data from the other two involved vehicles but then that wouldn’t be in keeping with the focus of this case problem’s design. www.collisionpublishing.com
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The implications of the CRASH3 uniaxial structural response model and the nature of available collision test data in regards to work-energy relationships for Jai Singh oblique impacts Biomechanical Engineering Analysis & Research, Inc.
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bstract Presented in the subject work is an investigation into the theoretical basis for the tangential correction factor utilized in the internal work absorbed formulation of the CRASH3 model, for oblique collisions, in light of the implications of the uniaxial nature of the structural response model and the nature of available controlled collision test data. Implicit in the original CRASH3 derivation is the treatment of the resultant collision force vector, for an oblique impact, based upon the component of the collision force in the normal direction to the deformed vehicle surface, as being along the relevant undeformed vehicle principle axis. The correction of this limiting assumption produces a collision force decomposition that mirrors the collision impulse decomposition found in planar collision mechanics formulations. The uniaxial nature of the empirical
structural response model, relating the peak collision force to the residual damage depth, while precluding the ability to explicitly model force and deflection in the induced damage region, presents a more pressing problem in regards to both the original CRASH3 formulation and the nature of available controlled collision test. The latter is predicated on the provision of residual damage depths along the undeformed vehicle relevant principle axis. As a result, for a uniaxial load path, the stiffnesses are quantifiable in axial compression only and with the transverse displacement of points on the geometry boundary treated as being constrained to zero. Not only does this preclude the quantification of the component of collision force vector in a normal direction, when the normal is not axial, for an oblique impact, but reduces the workenergy relationships for the oblique case to those of the non-oblique case.
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n i y t n i a t r s e e t c a n U m i d t n t s a E a s d n e e r e k o p a r S T r E g s n t i s v e i T r d i s De k e S n er e h m c c s i F . fro dent S C m a i i ill c W Ac
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To make an estimate of initial speed from evidence gathered at the scene of an accident, an investigator must determine the path a crashed vehicle took, the resistance acting on the vehicle along that path, and the distance over which that resistance acted. Measuring distance is ordinarily a straight forward task, greatly aided by the use of precision survey instruments. However, even where there is observable evidence by which to determine the path, estimating the resistance that a car developed during a pre-impact skid, or a chaotic post-impact slide or tumble to final rest, may introduce significant error. A series of roadside experiments, consisting of several skid-to-stop tests, are often conducted at the scene in an attempt to determine how much 44 Collision Magazine - Volume 10 Issue 1
friction a fully braked vehicle can develop on that road surface. This paper demonstrates that the friction values obtained from such skid-tostop tests, and the speeds derived from them, are likely to be invalid or unreliable. Invalid for two reasons: first, because a test car cannot duplicate the deceleration rate of the accident car except by random chance, and second, the average deceleration value calculated by a skid computer does not isolate the quantity the investigator seeks to measure: specifically, the kinetic tire to road coefficient of friction, (µk). The results are also unreliable because, as a statistical analysis of such empirical tests will demonstrate, the resulting range is so large as to be “little better than guessing”. 13
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During each skid-to-stop test the deceleration rate is typically sampled and recorded as many as one-hundred times per second by a skid computer mounted on the windshield of whatever vehicle the investigator may be using. The raw data is critically damped to
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Many accident reconstruction reports will involve at least one of these two equations. Eq.1 is often referred to as the speed equation, Eq. 2 as the critical speed yaw, or CSY equation.
eliminate extraneous signal noise and filtered to smooth out averaged values. These averaged values will then be adjusted by the computer for the slope of the road to produce a baseline drag factor. To calculate speed, the adjusted drag factor is then used in one of two equations, depending on whether the observed path of the crashed vehicle is linear or curvilinear: Eq. 1 Linear: d = length of observed skid marks f = adjusted drag factor
Relevant court opinions will be linked to these skid test procedures. Required test protocols of recognized engineering authorities will be specified. Variables affecting test results will be identified. Sources of independent testing will be reviewed. And the practical question of “What difference will all this make in a speed estimate?” will be answered.
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efinitions
The definition of several terms is essential to framing this discussion. Vehicle Axis System
The S.A.E. international convention defines traction forces, either acceleration or braking, as longitudinal (Fx), acting along the x-axis. Cornering traction forces are lateral (Fy) and aligned with the y-axis.
Eq. 2 Curvilinear: r = initial radius of observed yaw marks f = adjusted drag factor
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A DIRTY TRICK BY A LAW OF PHYSICS, OR WHAT? Erik Carlsson This article is about a full-scale vehicle crash test that seems to have been made for no other reason than to teach a lesson to an automotive engineer who had the nerve to criticize a vehicle design that was subject to litigation. Be that as it may, the crash test backfired. What brought the issue to court was the extreme face and head injuries the driver of a car sustained in an offset head-on collision with a pickup truck. The collision, which was severe, happened in daylight on a busy two-lane two-way dry country road. Neither of the involved drivers was after the accident able to tell what happened 1. However, the accident was witnessed by two other drivers, one traveling behind the car, the other behind the pickup truck. Those drivers testified at the police investigation that followed that the traffic was moving at about 40 mph. They both had a clear view of the collision from their positions a short distance behind the accident vehicles. They saw the car drifting into the lane of the oncoming pickup truck a moment before the impact. Both accident vehicles rotated counterclockwise at the impact, the car about 150 degrees, and the heavier pickup truck about 120 degrees. Both vehicles deviated to the right following the impact, coming to rest a short distance from the point of impact. Although no one doubted that the accident was caused by the car driver failing to pay attention to the road, the maker of the car nevertheless ended up in court as a defendant. The issue raised by the plaintiff's legal team was the design of the steering wheel hub and column in the accident car. The car was of a model that for a period of time was one of the bestselling compact cars before airbags became mandatory. The car had a small steering wheel, with a centerpiece about the size of the palm of a hand that served as a signal horn button. The visible surface of the centerpiece was made of soft plastic, and looked rather 64 Collision Magazine - Volume 10 Issue 1
collision-friendly. However, directly underneath the thin centerpiece was the upper end of the solid steering wheel shaft. Due to the severe crush of the car's front end at the impact, the rack and pinion steering gear and the firewall were displaced a substantial distance rearward, pushing the steering wheel rearward and upward, striking the face of the small driver. [It is of interest to note that the defendant carmaker's legal team did not raise the issue as to whether the driver was wearing her seatbelt, which was of a type equipped with a tension reliever. This type of belt had at the time been heavily criticized by the NTSB because those belts had been found to permit excessive forward movement of the restrained occupant's upper torso in frontal collisions. Note: This is the type of seatbelt that was described in "Think of a Number, Then ….," Fall 2013 issue of Collision.] The defendant carmaker retained as its expert witness an engineer who had previously been a designer at the company, and who in fact was said to be the designer of the steering wheel and column in the accident vehicle model. He testified at his deposition that the car's steering system met the FMVSS 203 requirement, which is that the resulting impact force must not exceed 2,500 pounds when the steering wheel is struck with a block of wood simulating a human chest, with the block moving at a speed of 15 mph. He also made the rather surprising statement that "a couple of inches of supersoft [sic] foam would not have made a difference" when he was shown several different steering wheels removed from other vehicles that all had deeply recessed energy-absorbing hubs. The engineer retained by the plaintiff's legal team addressed in his report the danger of a vehicle design lacking an effective energy-absorbing steering wheel hub and a fully collapsible steering shaft and column.
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He further made a comment in his report that the car driver swerved to the right before the accident, though too late to avoid the collision. The badly bent steering gear rack was jammed in a position corresponding to half a turn to the right of the steering wheel from its straight ahead position. Half a turn is just about how much a driver with both hands on the steering wheel can be expected to turn it with a rapid movement of the hands, he wrote in the report. While the comment about the car driver swerving to the right just before the impact was not addressed as being of significance in the engineer's report, the defendant carmaker's own expert nevertheless challenged the statement, claiming the car driver could not have steered to the right before the impact. If she had, he claimed, the pickup truck would have deviated to the left, not right, and continued front end first following the impact. His explanation for the position in which the steering rack was jammed was that the large rearward displacement of the left front wheel and suspension displaced the steering rack in such a way that the right front wheel turned to the right. Computer simulation is always a useful tool, or is it? To show that the car driver could not have swerved to the right before the impact, the defense expert included in his report the result of a computer simulation that showed the pickup truck continuing front end first and deviating to the left following the impact. The computer simulation was naturally based on the law of conservation of linear momentum. The reasoning therefore was that had the car driver steered to the right before the impact, the car would have gained some momentum towards the side of the road that was to the right of the car and thus to the left relative to the pickup truck's direction of travel. At the impact, the car lost almost all its speed, thereby also almost all of its momentum. The lost momentum was all transferred to the pickup truck, which thus gained the momentum towards the side of the road that the car lost. The pickup truck therefore had to deviate to its left following the impact. (At least in theory!) In the computer simulation both vehicles moved in straight lines towards each other, with the two lines of movement intersection each other at an angle of 10 degrees (or, if one so prefers, 170 degrees). Hence the
car was shown as initially being well into the pickup truck's path while gradually moving to its right so as to simulate the car driver's attempt to get out of the way for the oncoming pickup truck. The simulated vehicles collided with a small overlap and with the car's rear end intruding much farther into the pickup truck's path than its front end. Thus, if the simulation correctly depicted the accident, the car driver could not have avoided a collision or a sideswipe anyway by swerving to the right unless she had managed to get the car's front bumper to clear the pickup truck's bumper by some two feet. This seems to contradict the statements by the two drivers who saw the accident. They saw the car drifting into the lane of the oncoming pickup truck just before the collision, not that the car went far into that lane and then started to move back towards its correct lane before the impact. Nor can the comment by the plaintiff's engineer that the car driver swerved to the right just before the impact reasonably be interpreted as meaning that the car's rear end in such a case had to be much farther into the wrong lane than its front end. Garbage In, Garbage Out [GIGO.] The perhaps most interesting aspect of this case is that the plaintiff's legal team did not raise the issue of the defense expert in his computer simulation very clearly misrepresenting the accident scenario by placing the car's rear end, and thereby also its Cg, farther into the pickup truck's lane than what can reasonably be deduced to have been the case at the accident. Not even the ten-degree angle with which the two directions of lines of travel intersected each other in the computer simulation could be said to truly represent the accident scenario. This angle was according to the carmaker's engineer based on a sketch that depicted the accident vehicles at the point of impact, but the proportions of the vehicles in the sketch were such that it was obvious that the sketch had not been drawn to scale! [The actual angle between the directions of movement by the two accident vehicles at the impact was never established.] Instead of challenging the input data used in the computations, the plaintiff's legal team dismissed the defense engineer's computer simulation as merely GIGO, a term often used in the early days of computing.
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Analysis and Performance of a Booster Seated 6 Year Old HIII Anthropomorphic Test Device When Utilizing Seat Belt Cinching For Lap Slack Control Michael T. Vecchio SafetyWorks – Safety Services
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ing children in booster seats and whether there was There is a paucity of data in regard to how seat any safety benefit for this kind of application. From belts behave in actual seating and real world our perspective this clearly addressed a way that assists automotive environments. The vast majority being in-position without being intrusive. of current understanding is derived from test protoBesides providing a way to stabilize children sitting in cols that do not accurately reflect real world seatbelt booster seats, CG-Lock based lap belt cinching techuse. While there is much data to substantiate the efnology also seemd to consistently allow the occupant fectiveness of seatbelts, there are many instances, for to sit comfortably in crash-position at all times, as if instance, where people ligitmately "wearing a seatyou had just donned your seatbelt. bellt" are ejected from the vehicle. As a result of this, there must be other effects when wearing seatbelts All testing was performed comparatively, using curthat can occur. Current seatbelts are not designed to rent design seat belts with buckle pretensioners. The keep the occupant in position. They are designed to specific test components can be found in Appendix C. be donned by an occupant in-position. Whether the occupant stays in-position is usually not examined In practical terms, the utilization of this restraint in certfication testing. This can be especially true for strategy allows complete freedom for the child in the upper body torso loop during normal driving and child occupants. use, while preventing lap belt slack from developing A series of tests were conducted using a CG-Lock lap- around the pelvis. During a crash event the pelvis is belt cinching device to determine the effect of being pre-restrained while the torso loop becomes locked as in-position on a booster seat compared to being out of it normally would by the inertial retractor. The effects position when seated on the same booster seat. Data of this restraint strategy in terms of slack removal and was collected for a standard mid-size seating environ- occupant response are examined. This paper examment using FMVSS 213 parameters and is examined ines the utility and possibilities of this concept both and analyzed for both in-position and out-of-position for crash safety and child stability. When installed situations. The testing quantified this difference for properly, it has been reported that children using the the 6 Year Old HIII ATD when seated in a booster "CG-LockTM” based technology do feel more comseat. fortable because they ride more stably since there is no tendency for the cinched seat belt system to loosen The tests demonstrated that there is a statistically and the seat to tip during vehicle maneuvering and relevant and significant difference in terms of injury cornering. probability between in-position and out of position. The data presented in this paper were developed in Possibilities for a restraint strategy that addresses this the pursuit of making the current continuous loop issue are explored in this article. slip tongue seat belt systems more effective in terms of improving booster seated child passenger stability. ntroduction TM A device based on “CG-Lock ” seat belt cinch- A system was proposed and patented which would aling technology is utilized in this study as well as low the lap loop of a continuous loop system to be the second generation CG-Lock lapbelt cinching “locked” at a comfortable level of snugness, while the device. This device and how it attaches to a seatbelt “torso loop” remained free to “reel” from an inertial buckle is shown in Appendix C. The reason the CG- locking retractor and as a result would perform as Lock, a performance driving add-on, was chosen is that originally designed. Also, this eliminated the need it had been getting so many testimonials from adult to engage the ALR, auto locking retractor, sometimes drivers in regard to its injury preventing attributes in utilized in the rear seat which most children feel is too vehicle crash events that the question emerged as to restrictive, as it restricts the complete seatbelt torso the effectiveness of such an add-on device for stabiliz- and lap paths.
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A Method to Establish Delta-V and Collision Force in a Two-Vehicle Collinear Collision where Stiffness Data for One of the Vehicles is not Available Jai Singh
Biomechanical Engineering Analysis & Research, Inc. 82 Collision Magazine - Volume 10 Issue 1
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The subject work focuses on the development of the deterministic equations for quantifying the initially unknown closure and separation phase stiffnesses for one collision partner, in a two collision partner system, in which each collision partner is modeled using the single degree of freedom approach coupled with a uniaxial linear-linear load-unload structural response model and for which the stiffnesses for one collision partner are known and the coefficient of restitution is estimated. Also presented, as functions of the initially known and estimated parameters, are the closed form solutions for the closing velocity, separation velocity, the change in velocity for each collision partner, the duration of both closure and separation, and the time-parametric kinematic response relationships. A worked example is also provided.
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The treatment of the structural response of a motor vehicle subject to collision loading as being uniaxial represents a well-established modeling methodology in the field of motor vehicle accident reconstruction. This approach is perhaps most clearly evidenced when it is coupled with both a single degree of freedom model for each collision partner and colinearity. When contextually apt (e.g. in-line head-on or front-to-rear impacts), this modeling methodology greatly simplifies the analytic endeavor. The inertial frame of reference, if parameterized by a rectangular Cartesian coordinate reference, can be chosen to have its principal axes aligned in a time-invariant manner, with respect to the collision, along the aligned axes of the collision partners. This mitigates the necessity for the explicit employment of coordinate transformations when working between the inertial frame of reference and the local frame of reference associated with each collision partner. If the structural response ‘element’ of each collision partner is taken as being aligned along the relevant principal axis of each collision partner, the same argument holds for the transformation of the load bearing response to the local frame of reference as it did for the local frame of reference to the inertial frame.
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d e s a B � o e d i V t n e d i n c o i c t A c u r t s n o a i c s e A R s n a r T of ight 235 Fl Adam Cybanski Gyro Flight and Safety Analysis
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ideo cameras are everywhere in the modern world. Although sales of camcorders and photographic cameras (which include the ability to record video) have been decreasing, there have been massive increases in the number of other devices that can record video. GoPro camera sales have doubled every year since they were first released, and the number of cell phones and tablets (all with video recording capability) in the US has exceeded 300 million, greater than the population of the country. Car dashboard cameras are selling well, and their popularity continues to rise as price decreases. Consumers install these portable video cameras in their vehicles to record accidents, monitor their vehicles while away, capture road trips, and document employee driving. The proliferation of these cameras is illustrated by the fact that the fatal crash of TransAsia Flight 235 was caught on three separate automobile dash cameras.
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Many people do not realize the amount of useful data that can be derived from a short ten second video. With identifiable features, a video analyst can determine the speed, location, heading, acceleration / deceleration, rate of turn of the camera (and that of the vehicle it is mounted in) at a rate of up to 29 times per second. In addition, the same data can be obtained on other vehicles within the field of view of the camera. The accuracy of the derived data depends on the distance from the camera to objects of interest, but can match or exceed GPS accuracy. Whether captured from a camera mounted in a car, a drone flying overhead, or a pedestrian holding a cell phone, analysis of video can produce detailed and useful information for an accident reconstruction. Video motion analysis is based on proven fundamentals of photogrammetry, matchmoving, geolocation, and timedistance speed measurement. Photogrammetry is the science of making measurements from photographs, and is employed to first determine the location and orientation of the camera based on references visible in the image, then to determine the location and orientation of other objects in the image, given the camera position. Matchmoving, also known as camera tracking, is the process of analyzing a video clip to determine camera motion in three dimensions, and that of moving visible objects in the scene. Time-distance speed measurement has been used by law enforcement for decades, initially using reference objects a fixed distance apart, then using systems like the Visual Average Speed Computer And Recorder, and using aerial surveillance of ground features. Geolocation is the determination of real-world geographic coordinates of objects, and is conducted for all identifiable features in a video. In recent years, new technologies have improved capabilities for analyzing video. Geographic Information Systems like Google Earth and Streetview make it quick and easy to identify landmarks from a video, then determine a pre-
cise latitude, longitude, and altitude for each point. The amount of cameras has dramatically increased the chances that an event will be caught on video. Software has been developed for the motion picture industry that facilitates the precise analysis of captured video, and computer hardware continues to improve, so that the large number of calculations required for photogrammetric video analysis can be carried out quickly and efficiently. In recent years, this type of analysis has been used in aviation accident investigations. A Canadian F18 fighter aircraft crashed at an air show in Lethbridge, Alberta, and the video of the accident was analyzed in order to help determine the cause of the crash. Footage from pole-mounted ramp security cameras and onboard dash/cockpit cameras has been analyzed to reconstruct aircraft flight paths in support of several international accident investigations. Recently, analysis of a handheld video in a helicopter accident revealed pertinent data for the investigation, including distances, speeds, accelerations, and other parameters to determine the detailed accident sequence, and was employed in a 3D visualization of the accident. The visualization matched the original captured video, further validating the analysis conducted. In the crash of TransAsia 235, dash cam video from several automobiles was analyzed in order to determine the velocities, tracks and orientation of air and land vehicles. Prominent features such as road markings, lamp posts, and corners of buildings were tracked in matchmoving software in order to calculate camera motion. These features were positively identified in Google Earth / Streetview, and their precise 3D coordinates were determined. This survey data was imported into the software, then the camera solution was oriented and scaled, producing a geolocated 3D point cloud of the surrounding environment. Prominent features of the aircraft and visible ground vehicles were also tracked and oriented/scaled from engineering measurements so that their motion was also part of the 3D scene. The calculated camera and object motions were analyzed to determine the actual positions, orientations and velocities of the vehicles. The derived data was validated by comparing it against vehicle performance information, through cross checks against reference vehicles, and by visualization, and showed that this analysis methodology can support or prove equivalent to current analysis methods using traditional data recorders.. Video analysis represents a new tool with significant potential for the modern traffic accident reconstructionist. It can provide precise, detailed information in cases where an EDR is not available, or can be used to augment EDR data. Video footage has traditionally been qualitative in nature, but the methodology described herein shows that it is also a good source of quantitative data for an investigation, making it invaluable for accident reconstruction.
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Three car, in-line crash analysis with CDR Data Rusty Haight Collision Safety Institute
Foundation for the Analysis Having reviewed the photos of the involved vehicles, it should be clear that the F-150 sustained front-to-rear damage, the Corolla sustained rear-to-front as well as front-to-rear damage and the RAV4 sustained rear-tofront damage. The severity of the rear-to-front damage on the Corolla is significantly greater (without assigning a specific magnitude to it at this point) than its frontto-rear damage. The damage to the rear of the RAV4 suggests something of an underride such that the front of the striking vehicle (we may conclude it is the Corolla not the F-150) went somewhat under the rear of the RAV4 and that there was an offset to the relative left side of the lane/involved vehicles. Correspondingly, the center and right front (from the driver’s perspective) of the Corolla exhibits what would be consistent with it having underrode the RAV4. The damage observed on the front of the F-150 is largely to the center and right front of the truck at and above the bumper level. The damage to the rear of the Corolla is widely distributed across the width of the entire rear end and induced damage extends essentially to the rear doors. The damage patterns, generally, are consistent with the most severe impact in the sequence being between the front of the F-150 and the rear of the Corolla and then the relatively less severe impact being between the front
of the Corolla underriding the rear of the RAV4. The damage is generally consistent with the description offered by the involved drivers in terms of their description of their order in the road in the relevant direction of travel. The first issue which might then be addressed then is: what is the order or sequence of the impacts and “who hit whom first?” To that end, the CDR Tool report might prove useful. While a party or witness might have perceived or offered the recollection of a single or of multiple impacts, their observations or subjective impressions/beliefs may or may not fit with the objective information found on/ from the vehicles as a function of damage or in the CDR Tool report. Here, for this case study, the focus is on application of the CDR Tool report in a crash analysis and while not excluding a further analysis of the damage which might be made by the reader by review of additional photos or as a function of a hands-on vehicle exam, we turn our attention to the CDR Tool report. CDR Tool Report Going into any analysis using CDR Tool retrieved/reported data, one of the first things one has to do - as it relates to the CDR data - is to figure out if all or part of the data is or is not associated with the crash/event being examined. Leading into that, of course, one would want to review the CDR Tool report’s Data Limitations text keeping in mind that the Data Limitations may not
Figure 1: CDR File Information 94 Collision Magazine - Volume 10 Issue 1
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be only the source of information one might need in an evaluation. For example, for some systems, the CDR Program Help file might provide additional insight into nuances of a given system. Having first contemplated the contents of the Data Limitations text found in the CDR report for the Corolla involved in this crash, we turn to the CDR File information data table on page 1 of the report and find that the report contains information associated with three “Front/Rear” events (Figure 1). In that regard, in the Data Limitations text we find these passages: “...The airbag ECU records data for all or some of the following accident types: frontal crash, rear crash, side crash, and rollover events. ... The airbag ECU has the following recording pages (memory maps) for each accident type to store event data: three pages for frontal or rear crash, ...” There are other similar passages in the Data Limitations text consistent with these but, for the moment, by inference, we can deduce that the system is capable of differentiating between frontal and rear crashes and that the listing in the File Information data table indicates that the three recorded events are individually frontal or rear events and the term “front/rear” is not used to specify a direction in that context. That is to say, the designation “front/rear” should not be inferred to mean, for example, “front-to-rear” or “front-and-rear.” In this context, the use is indicating that the aribag control module’s EDR subcomponent has recorded event which are “front or rear” events and may then be recorded separately in each of the three memory pages available to the Event Data Recorder (EDR) subcomponent. Next, we might look to the “Front/Rear Event Record Summary at Retrieval” data table (Figure 2) which lists the currently recorded and recovered events and identifies the number of times the module has experienced a “trigger (TRG)” threshold. A trigger threshold is analogous to what CDR Data Analysts have seen in CDR Tool reports for GM vehicles as “algorithm enable” or the point where the airbag control module (ACM) “wakes up” and begins running the deployment decision making process. As outlined in the 2013 CDR User’s
Summit presentation “Toyota EDR Accuracy - deltaV, Speed, etc.” (by Bob Anderson and Rusty Haight), the “trigger threshold” for Toyota systems such as that found in the Corolla here is 2g along the longitudinal axis. While there has been some discussion within the community about a frontal negative longitudinal bias associated with Toyota modules, testing discussed in that presentation and again in a data review and presentation at the 2015 CDR User’s summit (same authors) shows that the observed 2g trigger threshold holds true for Toyota systems and that a calibration-based bias on individual systems may impact the reported delta-V (particularly in lower delta-V events) when compared to instrumentation which may be used in a crash test. Later research by others has also identified this same trend. Specific to this instance, we find that the Toyota ACM has recorded three events in total (triggers or TRGs1, 2 and 3) and all are, consistent with the naming convention of the data table, identified as “front/rear” events however specific directionality/polarity (from the front as opposed to from the rear) isn’t found in Figure 2. Even with the backdrop of an understanding of the damage to the involved vehicles in mind, those entries then don’t directly address the first question in the case problem: 1. What is the order of the impact(s)? Or, which vehicle hit which vehicle first? What information supports your conclusion(s)? For this Toyota airbag control module (ACM), the order of the recorded events is identified by two data elements: (1) trigger (TRG) count and (2) at least partly by way of a chronological naming convention descriptor (i.e.: “Most Recent” or “First Prior” event). This is also addressed in the Data Limitations text in the passage: “... The data recorded by the airbag ECU in the event of a frontal/rear crash includes information that indicates the sequence and interval of each previously-occurring frontal/rear crash event.
Figure 2: Front/Rear Event Record Summary at Retrieval www.collisionpublishing.com
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