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Accident reconstructionists rarely have complete data with which to determine vehicle speed, and so the true value must be bracketed within a range. Previous work has shown the effect of friction uncertainty in determining speed from tire marks left by a vehicle in yaw. The goal of the current study was to assess improvements in the accuracy of vehicle speed estimated from yaw marks using progressively more scene and vehicle information. Data for this analysis came from staged S-turn maneuvers that in some cases led to rollover of sport utility vehicles. Initial speeds were first calculated using the critical curve speed (CCS) formula on the yaw marks from the first portion of the S-maneuver. Then computer simulations were performed with progressively more input data: i) the complete tire marks from the whole S-maneuver, ii) measured vehicle mass, iii) measured suspension stiffness and damping, and iv) measured steering history.

Data downloaded from event data recorders (EDRs) integrated into the airbag systems of passenger vehicles can be key evidence for collision investigators. Often the EDR data includes information about the severity of the collision in terms of the longitudinal and lateral speed changes experienced by the vehicle. Previous studies have shown that for collisions with small lateral speed changes, the accuracy of the reported longitudinal speed change varies with manufacturer and magnitude. The goal of this study was to quantify the accuracy of EDR-reported speed changes in high-speed angled collisions with larger lateral speed change components. Data from 25 crash tests conducted for the National Highway Traffic Safety Administration’s (NHTSA’s) Oblique Offset Frontal Impact Research and Development Program were used in this study.

The repeatability and accuracy of front and rear speed changes reported by Toyota’s Airbag Control Modules (ACMs) have been previously characterized for low-severity collisions simulated on a linear sled. The goals of the present study are (i) to determine the accuracy and repeatability of Toyota ACMs in mid-severity crashes, and (ii) to validate the assumption that ACMs function similarly for idealized sled pulses and full-scale vehicle-to-barrier and vehicle-to-vehicle crashes. We exposed three Toyota Corollas to a series of full-scale aligned frontal and rear-end crash tests with speed changes (ΔV) of 4 to 12 km/h. We then characterized the response of another 16 isolated Toyota ACMs from three vehicle models (Corolla, Prius and Camry) and 3 generations (Gen 1, 2 and 3) using idealized sled pulses and replicated vehicle-to-vehicle and vehicle-to-barrier pulses in both frontal and rear-end crashes (ΔV = 9 to 17 km/h).

The accuracy of collision severity data recorded by event data recorders (EDRs) has been previously measured primarily using barrier impact data from compliance tests and experimental low-speed impacts. There has been less study of the accuracy of EDR-based collision severity data in real-world, vehicle-to-vehicle collisions. Here we used 189 real-world front-into-rear collisions from the Crash Investigating Sampling System (CISS) database where the EDR from both vehicles recorded a severity to examine the accuracy of the EDR-reported speed changes. We calculated relative error between the EDR-reported speed change of each vehicle and a speed change predicted for that same vehicle using the EDR-reported speed change of the other vehicle and conservation of momentum. We also examined the effect of vehicle-type, mass ratio, and pre-impact braking on the relative error in the speed changes.

The objectives of this study were to use Finite Element (FE) simulations to predict the crush profile resulting from frontal pole impacts and to compare the results of the FE simulations to existing reconstruction methods. A 2001 Ford Taurus FE model created by the National Crash Analysis Center (NCAC) was used to simulate four pole impact tests performed by the Insurance Institute of Highway Safety (IIHS) involving the same generation of Ford Taurus. The FE crush profiles show good correlation to the physical tests. The maximum crush was predicted within ±3% for three of the tests and was under predicted by 7% in the fourth test. The same FE model was then used to simulate 22 more pole impacts to study how impact speed and lateral pole offset from the centerline affected maximum crush. At impact speeds of 32 km/h, the maximum crush did not vary by more than 4 cm for different pole locations ±500 mm from the vehicle centerline.

Passenger vehicle bumpers are designed to reduce collision damage. If colliding bumpers are not vertically aligned, their effectiveness is reduced and the resulting damage increases. Two bumpers of similar static design heights may become misaligned due to bumper dive caused by one or both vehicles pitching forward due to braking. Previous researchers have quantified bumper dive and how it changed with passenger vehicle designs. Currently there are limited data available to quantify the mean, variance, and distribution of bumper dive for modern ABS-equipped vehicles. We conducted maximum braking tests using 3 late-model minivans/CUVs (crossover utility vehicles) and 9 late-model sedans on contiguous dry asphalt and concrete road surfaces. Between 16 and 23 tests were conducted for each vehicle and all tests were conducted from an initial speed of about 65 km/h (40 mph). A laser distance sensor mounted to the front bumpers measured bumper height throughout each test.

Quantifying the energy associated with vehicle damage is the basis of common methods used to reconstruct car crashes. This study sought to characterize the relationship between crush and energy for the front and rear surfaces of a passenger car. Nine stationary barrier crash tests and one aligned car-to-car test were conducted using several cars of the same model with impact speeds ranging from 4.3 to 15.2 m/s generating as much as 0.47 m of crush. The results revealed a linear speed-crush relationship for front and rear car surfaces and a restitution coefficient that decreased from a maximum of 0.33 at low speed to a relatively constant value of 0.15 for crush levels above 0.2 m. Crush coefficients derived from the crash tests were compared to the coefficients from three other sources: i) default values from the CRASH3 computer program, ii) values from a published database and iii) values derived from an assumed damage threshold value and an NHTSA high-speed crash test.

Numerical parameters describing suspension stiffness and damping are required for 3D simulation of vehicle trajectories, but may not be available. This paper outlines a simple, portable method of measuring these properties with a coefficient of variation of 5% on stiffness. 24 of 26 vehicles tested were significantly stiffer in roll than pitch, complicating analyses with models that don't include anti-roll. Suspension parameters did not correlate with static wheel load distribution, and damping coefficient did not correlate with natural frequency. Computer simulations of the speed required to initiate rollover in an S-curve were highly sensitive to the suspension parameters used. When pre-impact tire marks and rollover distance were considered, the simulations became almost insensitive to suspension parameters.

Wheel separations from passenger cars, light trucks and RV’s are reviewed, and the causes are analyzed through component and full vehicle testing. Wheel separations have led to injuries from the vehicle losing control, from the separated wheel colliding with another vehicle or pedestrian, or from another vehicle maneuvering to avoid the projectile. Separations are often soon after a wheel installation. This paper describes the physical evidence often seen after a wheel separation. Interpretation of the evidence through analysis and experiment indicates a low clamping force by the wheel studs and nuts leads to nut detachment or stud fatigue fracture. A low clamping force can result from improperly tightened nuts or from a loss in clamping force due to a very small amount of wear in the mating components clamped by properly tightened studs and nuts.

Vehicle rollovers generate complicated damage patterns as a result of multiple vehicle-to-ground contacts. The goal of this work was to isolate and characterize specific directional features in coarse- and fine-scale scratch damage generated during a rollover crash. Four rollover tests were completed using stock 2001 Chevrolet Trackers. Vehicles were decelerated and launched from a rollover test device to initiate driver's side leading rolls onto concrete and dirt surfaces. Gross vehicle damage and both macroscopic and microscopic features of the scratch damage were documented using standard and macro lenses, a stereomicroscope, and a scanning electron microscope (SEM). The most evident indicators of scratch direction, and thus roll direction, were accumulations of abraded material found at the termination points of scratch-damaged areas. Abrasive wear mechanisms caused local plastic deformation patterns that were evident on painted sheet metal surfaces as well as plastic trim pieces.

Bicycle computers record and store global position data that can be useful for forensic investigations. The goal of this study was to estimate the absolute error of the latitude and longitude positions recorded by a common bicycle computer over a wide range of riding conditions. We installed three Garmin Edge 530 computers on the handlebars of a bicycle and acquired 9 hours of static data and 96 hours (2214 km) of dynamic data using three different navigation modes (GPS, GPS+GLONASS, and GPS+Galileo satellite systems) and two geographic locations (Vancouver, BC, Canada and Orange County, CA, USA). We used the principle of error propagation to calculate the absolute error of this device from the relative errors between the three pairs of computers. During the static tests, we found 16 m to 108 m of drift during the first 4 min and 1.4 m to 5.0 m of drift during a subsequent 8 min period. During the dynamic tests, we found a 95th percentile absolute error for this device of ±8.04 m.

Modern vehicles record dynamic data from a number of on-board sensors for events that could precede a crash. These data can be used to reconstruct the behavior of a vehicle, although the accuracy of these reconstructions has not yet been quantified. Here, we evaluated various methods of reconstructing the vehicle kinematics of a 2017 and a 2018 Toyota Corolla based on Vehicle Control History (VCH) data from overlapping events generated by the pre-collision system (PCS), sudden braking (SB) and anti-lock brake (ABS) activation. The vehicles were driven towards a stationary target at 32-64 km/h (20-40 mph) and then after the pre-collision alarm sounded the vehicle was steered sharply right or left and braked rapidly to rest. VCH data for PCS event were recorded at 2 Hz and for the sudden braking and ABS activation events at 6.7 Hz.

Vehicle rollovers are complex events that can be difficult to reconstruct. The goal of this study was to explore whether different vehicle trip models could identify when during the trip phase a vehicle possesses the dynamic conditions needed to rollover. We used three sport utility vehicles (SUVs) with either absent or disabled electronic stability control to conduct six tests involving a steer-induced control loss on a large flat concrete surface. Vehicle kinematics were measured using a GPS speed sensor, tri-axial accelerometers, tri-axial angular rate sensors, and both drone- and land-based video cameras. Four vehicle trip metrics were derived and evaluated using the vehicle dynamics between steer onset and the end of the trip phase. During three tests, one or more of the vehicle’s tires lifted off the ground but the vehicle did not roll. In the other three tests, the vehicle rolled.

Rollover crashes are complex events that generate motions in all six degrees of freedom (6DOF). Directly quantifying the angular rotations from video can be difficult and vehicle orientation as a function of time is often not reported for staged rollover crashes. Our goal was to evaluate the ability of using a match-moving technique and consumer-grade video cameras to quantify the roll, pitch and yaw angles and angular velocities of a rollover crash. We staged a steer-induced rollover of an SUV at 106 km/h. The vehicle was fitted with tri-axial accelerometers and angular rate sensors, and five consumer-grade video cameras (2 on tripods, 2 on drones, 1 handheld, ~30 fps) captured the event. Roll, pitch and yaw angles were determined from the video using specialized software.

Collision related data stored in the airbag control modules (ACM's) of Toyota vehicles can provide useful information to collision investigators, including both front and rear collision severity. Previous studies of ACM's from other manufacturers found that the devices underestimated the actual speed change in low speed frontal collisions. To quantify the accuracy and sensitivity of select 2005 to 2008 Toyota ACM's, in-vehicle crash tests and linear sled tests were performed in both front and rear impact orientations. A 2005 Toyota Corolla with five extra ACM's mounted in the right front seat position underwent a series of vehicle-to-barrier collisions with speed changes of up to 10 km/h. Next, the same six Toyota ACMs underwent a range of crash pulses using a linear sled. In all in-vehicle tests, the speed change reported by the ACM underestimated the actual speed change for frontal collisions, and overestimated the actual speed change for rear-end collisions.

Newer Toyota vehicles store information about more than 50 parameters for 5 s before and after non-collision events in the Vehicle Control History (VCH) records. The goals of this study were to assess the accuracy of VCH data acquired during Autonomous Emergency Braking (AEB) events and to investigate the effects of speed, acceleration, and system settings on AEB performance. A 2017 Toyota Corolla with Safety Sense P Pre-Collision System (PCS) was driven in a straight line towards a car-like target at different combinations of four speeds (20, 25, 30, and 40 km/h; or 12, 15, 19, and 25 mph) and three accelerator pedal positions (constant 30%, 40%, and 50% accelerator opening ratios) until the AEB system activated. The vehicle speed, vehicle acceleration, radar target closing speed, and radar target distance recorded in the VCH were compared to a reference 5th wheel. We found that errors in the VCH distance, speed, and acceleration data varied with the test conditions.

The Pre-Collision System (PCS) in Toyota’s Safety Sense package includes an autonomous emergency braking feature that can stop or slow a vehicle independent of driver input if there is an impending collision. The goals of this study were to determine how hazard characteristics, specifically radar reflector size and degree of target edge contrast, affect the response of the PCS, as well as to scrutinize tests wherein the PCS failed to stop the vehicle before impact. We conducted 80 tests with a 2017 Toyota Corolla driven towards a car-like target in a straight line and under constant accelerator pedal position, reaching about 30 km/h at the PCS alarm. Vehicle speed and distance to target at the alarm flag (ALM) and at times corresponding to three other system flags (PBA, FPB, and PB) were read from the Vehicle Control History records. Time to impact (TTI) at each flag was calculated and the distance between the stopped vehicle and the target was measured for each test.

Most collision reconstructions implicitly assume the same tire/road friction coefficient for all vehicles, despite evidence that friction varies between tires, surfaces, and individual trials. Here we assess the errors introduced by an assumption of a single, universal friction coefficient when reconstructing a collision where vehicles actually had different tire frictions. We used Monte Carlo methods to generate 20,000 synthetic two-vehicle impacts and rest positions using different, randomized friction coefficients for each vehicle and randomized impact speeds. These rest positions were then used to reconstruct both vehicles’ impact speeds assuming a single, common friction coefficient. High and low bounds on the impact speeds were reconstructed using high and low bounds on the common friction. We found that more than 97% of the true impact speeds were in the ranges reconstructed using upper and lower friction bounds.

The goal of this study was to use naturalistic driving data to characterize the longitudinal and lateral accelerations of vehicles making a left turn from a stop at signalized intersections. Left turn maneuvers at 15 intersections were extracted from the Second Strategic Highway Research Program (SHRP2) database. A subset of 420 traversals for lead vehicles that were initially stopped and negotiated their left turns unimpeded by oncoming traffic was used for the analysis. For each traversal, we extracted information regarding the driver’s sex and age, the vehicle type, the vehicle’s longitudinal and lateral acceleration, and on-board forward-facing video. From the video, we further extracted information about whether the road was dry/wet and if it was day/night, and from aerial photographs of the intersections we extracted the radius of each left turn path through the intersection.

The goal of this study was to use naturalistic driving data to characterize the motion of vehicles making right turns at signalized intersections. Right-turn maneuvers from 13 intersections were extracted from the Second Strategic Highway Research Program (SHRP2) database and categorized based on whether or not the vehicle came to a stop prior to making its turn. Out of the vehicles that did stop, those that were the first and second in line at the intersection were isolated. This resulted in 186 stopped first-in-line turns, 91 stopped second-in-line turns, and 353 no stop turns. Independent variables regarding the maneuver, including driver’s sex and age, vehicle type, speed, and longitudinal and lateral acceleration were extracted. The on-board video was reviewed to categorize the road as dry/wet and if it was day/night. Aerial photographs of the intersections were obtained, and the inner radius of the curve was measured using the curb as a reference.