Search Results

Relying on both general and case-specific examples, we used Monte Carlo analyses to explore how uncertainty can be calculated and how it varies for different measurements and different camera-, scene-, and vehicle-related properties. ...Video evidence in collision reconstruction has become a common foundation for vehicle position and speed analyses. The goal of this study was to explore how the uncertainty of these position/speed analyses is affected by various camera-, scene-, and vehicle-related properties. ...Overall, these findings show that uncertainty in video-based reconstruction analyses cannot be expressed as a universally applicable percent error; instead, the uncertainty of a measurement depends on the unique combination of camera, scene, and vehicle in a specific analysis.

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. ...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.

This paper quantifies uncertainty in the radius when it is determined by fitting a circular arc to three or more points. A Monte Carlo analysis was used to generate points on a circular arc given three parameters: number of points n, arc angle θ, and point measurement error σ.

This research provides valuable insight into the typical acceleration profiles of left-turning vehicles and the linear regression models developed here can be incorporated into accident reconstruction analyses of left-turning vehicles.

Accident reconstructionists rarely have complete data with which to determine vehicle speed, and so the true value must be bracketed within a range.

These test results will allow accident reconstructionists to better quantify vehicle speeds in snowmobile incidents in similar snow conditions.

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 results of these analyses provide insights into the best methods for reconstructing vehicle kinematics from VCH data and estimates of the errors associated with different reconstruction techniques.

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 study provides a better understanding of the effects of the pre-impact data timing for accident investigators.

This research provides valuable insight into the typical accelerations and speeds of vehicles during right-turn maneuvers, and the results are directly applicable to collision reconstructions.

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.

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.

With further refinement, testing and validation over a wider range of vehicles and conditions, these metrics could be useful in some rollover reconstructions for identifying when sufficient dynamic conditions are present during the trip phase for rollover to occur.

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.

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.

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.