Issuu

2016 CDR SUMMIT DVD

ollision C The International Compendium for Crash Research Volume 11, Issue 1

Soil-Tripped Rollover Crash

Female Occupant Kinematics in Low-Speed Rear End Collisions EDR Data from Ford Systems not CDR Tool Supported The Complete CDR Tool Version History collisionmagazine.com Volume 11 Issue 1 Sean.indd 1

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Contents

2016

Volume 11 Issue 1

inside 06

Letter From the Editor

features 08

The Accelerations Present During the Trip Phase of a Soil-Tripped Rollover Crash by: Nathan A. Rose and Neal Carter

The Older Lady Versus the Younger Lady: Female Occupant Kinematics in Low-Speed Rear End Collisions by: Lissette M. Ruberté, Billy S. Cox, Jr. and Susan Lantz

My Turn at the Wheel: Be Careful With What You Ask For It Might Bite You! by: Erik Carlsson

Streamlining Accident Investigation by: Larry Trojak

Using Ford EDR Pre-crash Stability Control System Data by: John Bruno and Richard R. Ruth

How Accurate are Witness Distance Estimates Given in Car Lengths? by: Nathan Rose, Neal Carter, John Kreisher, Martin Randolph, William Neale and David Danaher

Release History of Bosch Crash Data Retrieval Tool Software by: W. R. Rusty Haight

case study 24

Crash Data Case Problems by: W. R. Rusty Haight

Case Problem Solutions www.collisionpublishing.com

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The Accelerations Present during the Trip Phase of a Soil-Tripped Rollover Crash Nathan A. Rose Neal Carter Kineticorp, LLC

ntroduction Figure 1 depicts the vehicle motion typical of a high-speed, soil-tripped, single vehicle rollover. The scenario depicted in this figure involves the following events: (1) a driver inputs a rightward steer of sufficient severity to cause the vehicle to enter a yaw (clockwise, in the example below); oftentimes, the steering input that leads to a loss of control will have been preceded by other steering inputs; (2) the driver may input a counter-steer back to the left, but is unable to regain control; (3) at some point during the clockwise yaw, the vehicle leaves the roadway, the wheels furrow into the soil, and the trailing side tires lift off the roadway (the passenger’s side tires in the example below); (4) as this motion continues, the center of mass travels over the leading side tires, the leading side tires lift off the roadway, and the vehicle becomes airborne and begins rolling; (5) the vehicle rolls until its kinetic energy is dissipated and it comes to rest.

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A rollover crash like this one is often split into three phases for analysis – the loss of control phase or yaw phase; the trip phase; and the roll phase. During the loss of control phase, driver steering inputs – or perhaps some other external force – result in the driver losing control of the vehicle. The vehicle enters an unrecoverable yaw during this phase. The trip phase then begins when the trailing side tires of the vehicle lift off the ground. This phase ends when the leading side tires also lift off and the vehicle becomes airborne [Orlowski, 1989]. A number of mechanisms can cause a vehicle to trip and begin to roll. For example, a combination of tire forces and suspension effects from severe steering inputs [Larson, 2000; Wilson, 2007a and 2007b; Stevens, 2011], interaction between a tire or wheel rim and pavement [Marine, 1999], wheels furrowing into soil or sod [Cooperrider, 1990 and 1998; Asay, 2009 and 2010], and wheels impacting a curb [Jones, 1975; Cooperrider, 1990; Hughes, 2002]. The roll phase begins once the vehicle becomes airborne following the trip phase and continues to rollover until it comes to rest.

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s u s r e v y d a L : r y d e a L d l r e O g Thehe Youn t

s c i t a m e n i K t n a p u c d c n O E e r l a a e m R e F w-Speed Lissette M.oRxu, Jbre.ratnéd, o S. C n Lantz y L l l i B n i isions Susa Coll 34 Collision Magazine - Volume 11 Issue 1

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bstract

Traditionally, women and older adults have been underrepresented as test subjects in full-vehicle crash tests. Some studies have reported an increased incidence and duration of whiplash-associated disorders (WAD) for females compared to males. Females are generally thought to be at greater risk of experiencing initial symptoms of WAD at lower impact severity collisions than males. They have also been reported to have twice the risk of experiencing symptoms lasting longer than one month and twice the risk of injuries leading to permanent impairment compared to men. Older adults are often thought to have pre-existing conditions and other natural aging processes that may increase the risk of injury compared to younger adults under similar crash conditions. In low-speed vehicle collisions, occupants experience changes in velocity and acceleration levels that are typically low in magnitude. In this article, we present a review of the literature, as well as, new female occupant crash test data. This data adds to the body of literature regarding occupant kinematic response during collinear low-speed rear-end impact collisions. A series of eight low-speed vehicle-into-barrier impacts tests were conducted with two instrumented female volunteers aged 35 and 60 years. The volunteers, both authors of this paper and developers of the paper’s title, had similar gross anthropometry, representative of the mean body height and weight of the U.S. female population. The older lady was exposed to three consecutive rear-end collisions resulting in a change in velocity of up to 2.0 m/s (4.5 mph) while unrestrained.

The younger lady was exposed to five rearend collisions with changes in velocity of up to 2.6 m/s (5.8 mph). The younger lady was unrestrained in all but one test. Range of motion and orthopedic tests were performed by a chiropractor within hours before and three days after the subject test. No clinically significant differences were noted in the posttest evaluation of either subject. Neither subject complained of pain or injury at the three-day post-test follow-up examination.

Injury Risk, Severity and Symptom Duration. The most widely accepted parameter for defining the severity of a collision is the Delta-V or change in velocity experienced by a vehicle. Delta-V has been traditionally used as a predictor for occupant injury in vehicular collisions. Roberts, et al. (1993) compiled data from 20,000 collisions of passenger cars, light trucks and utility vehicles from the data contained in the National Accident Sampling Study (NASS) database. The authors observed, “The National Crash Severity Study (NCSS) by relating accident severity, expressed in terms of Delta V, with injury severity to the form of the Abbreviated Injury Scale (AIS) has provided an (sic) convenient means to start to quantify the relationships with may exist between injuries, their severity and the change in velocity in a collision.” AIS is an anatomically based scoring system that classifies individual injuries by body region on a scale of 1 to 6 (1 = minor and 6 = maximum). In low-speed rearend impact collisions, the majority of the symptoms or injuries claimed are classified as minor (AIS 1), and are non-life threatening. The authors concluded that the incidence of soft tissue injuries are shown to be related to the change in velocity in a collision.

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iterature Review

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. l e e h e w h t at n r u my t

BE CAREFUL WITH WHAT YOU ASK FOR IT MIGHT BITE YOU! by EriK Carlsson

his article is about yet another case in which a carmaker involved in litigation retained a resourceful testing laboratory to disprove the allegation by a law firm that represented an injured vehicle driver. And, as in the two other crash tests described earlier in Collision, even this crash test resulted in some red faces. The driver of a small car sustained serious spinal injuries when the roof of her car collapsed at a collision with a deer that jumped across the road. The deer partially entered the interior of the car due to the substantial rearward deformation of the front section of the roof. The accident happened at night on a country road that the driver had entered a moment before the accident. The speed of the car was therefore believed to have been well below the speed limit, 45 mph. The neck of the driver was subjected to excessive rearward bending which resulted in irrevocable injuries. (The driver, who was pregnant at the time, became a quadriplegic.) A law firm representing the injured driver filed a law suit against the car manufacturer, alleging that the roof of the car she was driving was too weak to offer a reasonable protection in a type of accident that could and should be anticipated, of which a collision with a jumping dear on a country road is very foreseeable, especially 50 Collision Magazine - Volume 11 Issue 1

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at night. As could be expected, the carmaker’s legal team maintained that the car model complied with all mandatory safety standards, and that the plaintiff’s allegation therefore was without merit. The plaintiff’s attorneys counteracted the defendant’s argument, and reasoned that the carmaker had an obligation to design the car in such a way that it offered its occupants a reasonable protection in accidents that should be anticipated. As an example of a much safer roof design than that of the subject vehicle, the attorneys referred to a car model where the manufacturer had demonstrated through FMVSS 208 dolly rollover tests that their cars had excellent roof strength. [The particular model mentioned by the attorneys is the same as the one depicted in the article “Don’t Look Too Closely!”, Vol. 10 Issue 2 of Collision.] The plaintiff’s attorneys also requested the defendant to supply manufacturing drawings of the roof of the accident vehicle model to be used as exhibit at trial in support of their allegations about the weak roof of the accident vehicle. The defendant carmaker’s technical staff may perhaps have shared the plaintiff’s negative assessment of the roof because after some legal wrangling and delay, the carmaker did supply roof drawings, but those drawings were of a model equipped with sunroof, which the ac-

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cident vehicle did not have. The sunroof was enclosed in a frame that was attached to both the windshield header and the side rails of the roof. Naturally, the framework behind the windshield header in the model equipped with sunroof added to the roof ’s resistance to a rearward force acting on the roof ’s front edge. The carmaker’s legal team no doubt expected that once the plaintiff’s attorneys had detected that the submitted drawings showed a roof that certainly had to be stronger than that of the plaintiff’s car, they would allege that the defendant in effect admitted that the roof of her car lacked a reasonable minimum strength. In what probably was an attempt to counteract such allegations, the defense team retained an expert witness from England, who had both engineering and medical training, and who in addition was very familiar with legal disputes about car safety here in the U.S. The expert wrote a detailed report in which he stated that had the roof of the plaintiff’s car been rigid, the front edge of the roof would have cut the deer in half at the impact. This would have caused the lower half of the deer to enter the passenger compartment. The plaintiff’s injuries would then have been worse. Hence the vehicle’s low roof strength was to her benefit, he opined. The defense legal team was apparently not convinced that the statement by their expert would be sufficient for the defendant carmaker to prevail in court. After all, most potential jurors could no doubt be expected to know that the plaintiff in this case sustained far more severe injuries than what happen to most drivers of cars hitting a deer, except in cases where a startled driver swerves to the side in an attempt to avoid the deer and instead hits a utility pole or a tree (or a house!)

A 17-year-old driver swerved to miss a deer, but hit this Hackettstown house. (photo courtesy of Jay Edwards - Star-Ledger) To demonstrate that the difference in roof design between the two car models would not have had any effect on the outcome of this accident, and that the plaintiff therefore would have been just as injured if she had been driving a car of the model referred to by the plaintiff’s attorneys, the defense attorneys retained a testing laboratory known for its abilities to meet expectations. In this case, to conduct a full-scale “deer” collision test with each of the two car models. The “car-to-deer” impact tests For the purpose of the requested tests, the testing laboratory created a “deer” by bundling together a number of PVC pipes, said to be partially filled with water and cotton so as to attain the weight of the actual deer, as estimated by the rescue staff that responded to the accident. At the impact tests, the “deer” was suspended in a vertical position, and at a height such that its center of gravity was about even with the front edge of the roof. The point of impact between the “deer” and the car roof was midway between the car’s centerline and the driver side A-pillar. The test speed was specified to be 50 mph. For reasons not explained, the crash tests were done without dummies in the cars even though the sole issue of the case was the extent of the driver’s injuries, not how the accident happened.

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Using Ford EDR Pre-crash Stability Control System Data Sgt. John Bruno Richard R. Ruth, P.E. Michigan State Police

Ruth Consulting LLC

his papers describes methods for the reconstructionist to use stability control system EDR data to: 1. Calculate the speed at impact more precisely than with pre-crash speed data alone

2. Calculate the distance to impact after first brake application or steering input in reaction to a developing situation 3. Calculate the lateral distance a vehicle moved during an evasive steering event based on a. Stability control lateral acceleration b. Yaw rate 4. Calculate the change in approach angle at impact relative to straight down the road The example used to explain the calculations is from a 2012 Lincoln MKZ (Figure 1), but stability control system data began to phase in for 2009’s and is in nearly all 2012 and later Ford event data recorders (EDR’s). The methodology can also apply to data found in some 2012 and later Toyota vehicles, and some 2006 and later Chrysler vehicles with yaw rate data. The example used is from an actual crash where a 2012 Lincoln MKZ rear-ended a large commercial vehicle in a snow storm. The speed control was set at 58 mph, but the driver took evasive action by braking and swerving to the left in the last one second prior to the crash. The issue under investigation was whether the MKZ driver reacted or not, and if so when the truck’s presence was perceived.

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Before any calculations are made we must verify the EDR recording is from our crash. The first page of the CDR report indicates a locked frontal event. It is a complete recording. The key cycles are 3760 at imaging versus 3759 at the time of the crash. The delta-V is -35.23 mph longitudinal and -3.02 lateral mph over 173ms, which is consistent with the last reported speed of 55.4 mph and the truck still moving, and the significant crush damage observed. The driver and

passenger airbags and pretensioners were deployed which is consistent with the physical evidence. The “Speed Control Telltale” was reported as “On” at -1 second and the reported 0% accelerator pedal position while maintaining a constant speed is consistent with the speed control being on. There is no doubt that this recording comes from this crash. The precrash speed, accelerator pedal, and brake data at 0.5 second intervals is shown in Figure 2.

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How Accurate are Witness Distance Estimates Given in Car Lengths?

ntroduction Accident reconstructionists generally agree that eye witness estimates of distance are often inaccurate. Robins [2001], for instance, observes that “in spite of the many converging cues available to humans to judge the separation distances and speeds of other objects, we perform poorly at such tasks.” Similarly, Olson [2003] observes that “witnesses’ judgements of distance in the usual measuring units are likely to be unreliable.” Despite the limitations of humans to judge distance, witnesses and drivers involved in car accidents are often asked to use the unit of a “car length” to estimate how far they were from another vehicle at some point prior to a collision. There seems to be some presumption that reformulating the

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question about distance in terms of “car lengths” somehow improves a witnesses’ or drivers’ ability to judge distance. Law enforcement officers and attorneys, in turn, sometimes use a witnesses’ or drivers’ distance estimates in terms of car lengths to reach conclusions about why an accident occurred or to evaluate whether or not a driver should have been able to avoid an accident. Accident reconstructionists also sometimes use these distance estimates to perform calculations related to following distance or accident avoidance. www.collisionpublishing.com

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Nathan Rose Neal Carter

John Kreisher Martin Randolph William Neale David Danaher Kineticorp, LLC

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tu e S

Cas

Case Problem Solutions

w. R. Rusty Haight

Collision Safety Institute Project: “2005 Pontiac G6” The solutions to this case problem based on a review of the data provided focuses largely on a reading of the Data Limitations and careful reading of the elements found in the report. This case problem and solution reinforce the idea that, to properly apply CDR Tool retrieved data, one has to consider appropriately linked data elements often beyond any one, single element. 1. The data for the recorded Non-Deployment reports a value for “Maximum SDM Recorded Velocity Change (MPH).” There are also data tables for “SDM Longitudinal (and lateral) Axis Recorded Velocity Change (MPH).” and “SDM Lateral Axis Recorded Velocity Change (MPH).” which report the delta-V relative to those axes. Start by comparing the delta-V from the data tables, of course in the context of the Data Limitations, with that reported as the “Maximum SDM Recorded Velocity Change (MPH).” Are there any apparent “differences?” If so, how might that be resolved? The question points to the data element “Maximum SDM Recorded Velocity Change (MPH)” found in the “System Status At Non-Deployment” data table (Figure 5) which reports a delta-V of 9.11mph (14.66km/h) and asks: how does that compare to the Data Limitations text relative to this element and the data found in the tables for “SDM Longitudinal Axis Recorded Velocity Change (MPH)” and “SDM Lateral Axis Recorded Velocity Change (MPH)” (Figure 6)? In Figure 2 (the Data Limitations text), we find these passages regarding delta-V: “... SDM Recorded Vehicle Velocity Change reflects the change in velocity that the sensing system experienced during the recorded portion of the event. SDM Recorded Vehicle Velocity Change is the change in velocity during the recording time and is not the speed the vehicle was traveling before the event, and is also not the Barrier Equivalent Velocity. ... Velocity Change data is displayed in SAE sign convention. ... Maximum Recorded Vehicle Velocity Change is the maximum square root value of the sum of the squares for the vehicle’s combined “X” and “Y” axis change 100 100 Collision Collision Magazine Magazine - Volume - Volume 11 Issue 11 Issue 1 1

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in velocity. If a CDR Printout user were to calculate resultant velocity change using X and Y axis time history data, the calculated value may be different than the Maximum SDM Recorded Velocity Change parameter value displayed in the CDR report. This is due to the rounding that occurs within the SDM while calculating the Maximum SDM Recorded Velocity Change value. ...” Next, we should look to Figure 6 for a resultant deltaV. The data tables are labeled “SDM Longitudinal (and lateral) Axis Recorded Velocity Change (MPH)” as referenced in the passage(s) above. The maximum value for delta-V on the Longitudinal axis shows -9.49mph (-15.27km/h) and for the Lateral axis 0.68mph (1.09km/h). Even a casual observer would notice that, yes, there is a difference between the “Maximum SDM Recorded Velocity Change (MPH)” (reported as 9.11mph) and the total one would calculate for a resultant delta-V using the “SDM Longitudinal (and lateral) Axis Recorded Velocity Change (MPH)” data sets. In that case, the resultant would be 9.49mph (15.27km/h). While that is, of course, the magnitude of the resultant delta-V, the direction (PDOF) would be about -4deg off the longitudinal axis. Relative then to the issue of polarity, the Data Limitations tells us that “ ... Velocity Change data is displayed in SAE sign convention. ...” Given that the only elements of those discussed which would, by themselves, have indicated polarity would be the “SDM Longitudinal (and lateral) Axis Recorded Velocity Change (MPH)” data sets we may assume that the polarity reference in the Data Limitations is actually specific to these data sets and not the “Maximum SDM Recorded Velocity Change (MPH).” In short then, polarity is not a “difference.” The magnitude of the calculated resultant delta-V compared to the “Maximum SDM Recorded Velocity Change (MPH)” is; however, a “difference.” The reported value found in the System Status data table (9.11mph) is, according to the Data Limitations text, “...the maximum square root value of the sum of the squares for the vehi-

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cle’s combined “X” and “Y” axis change in velocity. ...” One is left to wonder then how if the resultant were to be calculated in the same fashion from the data found in Figure 6, it would yield an answer of 9.49mph.

2. There is one recorded event; the Non-Deployment event. Based on the remainder of the data found in the report from the Pontiac, this module “saw” a total of how many related events?

The Data limitations touches on this point where it reads: “... If a CDR Printout user were to calculate resultant velocity change using X and Y axis time history data, the calculated value may be different than the Maximum SDM Recorded Velocity Change parameter value displayed in the CDR report. This is due to the rounding that occurs within the SDM while calculating the Maximum SDM Recorded Velocity Change value. ...”

The data reports one recorded Non-deployment event (Figure 1) and one “Associated Event Not Recorded” (Figure 3). That “observed” but not recorded event is identified as a “Non-Deployment” which preceded the recorded Non-Deployment (Figure 3).

Clearly it is different and it begs the question: how does rounding the maximum values in the “SDM Longitudinal (and lateral) Axis Recorded Velocity Change (MPH)” data sets result in a number greater than that found in the System Status summary “Maximum SDM Recorded Velocity Change?” Perhaps a clue is found in the verbiage of the Data Limitations text itself where it reads “... This is due to the rounding that occurs within the SDM while calculating the Maximum SDM Recorded Velocity Change value. ...” Where the “Maximum SDM Recorded Velocity Change” might be calculated then recorded in the SDM, the underlying quantities used (in the SDM) to make the calculation are not recorded and we are left to speculate what they might have been. In contrast, the quantities used to calculate the resultant using the “SDM Longitudinal (and lateral) Axis Recorded Velocity Change (MPH)” data sets may not be subject to the same rounding as was done in the SDM when the single maximum value was recorded. In the final analysis; however, is the “difference” between these quantities really a significant qualitative concern to the analyst? While opinions may vary, there is obviously a quantitive difference (the difference in the magnitude of the numbers themselves), but if one were reasonably working from a range for the delta-V in the first place (for example, adopting that the magnitude of the delta-V in this case was between 9 and 10mph rather than the arguably over precise 9.11 or even 9.48mph), the magnitude of the difference becomes effectively irrelevant. Undeniably, the difference is one to be aware of but the significance is of virtually no real consequence in the scope of a larger analysis particularly when one is or should be working with a range to start with.

3. Based on the data for the Pontiac as recorded and reported, there was an “observed” but not recorded event which would have had a delta-V of greater than _______ but less than _________ (select units as appropriate) and would have occurred within ______ seconds of the recorded event. How would this other event relate to the overall crash sequence as described? For the first part of this question, it would be far too easy to look to the Data Limitations text (Figure 2) and suggest that the delta-V of the not recorded but “observed” Not-Deployment would have to be at least 5mph (8km/h) where we find the entry: “... The minimum SDM Recorded Vehicle Velocity Change, that is needed to record a Non-Deployment Event, is five MPH. ...” However, a careful further reading of the entirety of the Data Limitations also tells us that “... The SDM can store up to one Non-Deployment Event. This event can be overwritten by an event that has a greater SDM recorded vehicle velocity change. ...” With this information, if we contemplate the “observed” but not recorded Non-Deployment (setting aside what we might know from the at-scene information associated with the human, vehicle and environment), we know that the not recorded event had to have been, at a minimum, sufficient to “wake up” the module (or the event would not have been “observed” and “associated”) but we should not loose sight of the idea that the requirement described in the Data Limitations calling for a 5 mph delta-V has to do with recording, not simply a “recognition” by the ACM that the event occurred. The ACM has to (1) “see” the event, (2) make a deployment (here a Non-Deployment) decision and then (3) make the record/don’t record decision based on whether or not the Non-Deployment qualifies for recording for that individual event. Here, we see that the delta-V which would qualify the event for recording is 5mph but the end result had to take into account the limit of only one Non-Deployment event ultimately being recorded and that a greater severity, later occurring Non-Deployment would overwrite a previous event.

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