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The critical curve speed formula used for estimating vehicle speed from yaw marks depends on the tire-to-road friction and the mark’s radius of curvature. 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. For each iteration, circular fits were performed using three techniques. The results show that uncertainty in radius is reduced for increasing arc length, decreasing point measurement error, and increasing number of points used in the curve fit. Radius uncertainty is linear if the ratio of the standard deviation in point measurement error (σ) to the curve’s middle ordinate (m) is less than 0.1. The ratio σ/m should be less than 0.018 for a radius found using a 3-point circular fit to be within 5% of the actual value 95% of the time.

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.

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.

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 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.

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.

Anti-lock brake systems (ABS) produce high levels of vehicle deceleration under emergency braking conditions by modulating tire slip. Currently there are limited data available to quantify the mean, variance, and distribution of vehicle deceleration levels for modern ABS-equipped vehicles. We conducted braking tests using twenty (20) late-model vehicles on contiguous dry asphalt and concrete road surfaces. All vehicles were equipped with a 5th wheel sampled at 200 Hz, from which vehicle speed and deceleration as a function of time were calculated. Eighteen (18) tests were conducted for each vehicle and all tests were conducted from a targeted initial speed of 65 km/h (40 mph). Overall, we found that late-model ABS-equipped vehicles can decelerate at average levels that vary from about 0.871g to 1.081g across both surfaces, and that deceleration levels were on average about 0.042g higher on asphalt than on concrete.

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.