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Technical Paper

Accuracy and Sensitivity of Yaw Speed Analysis to Available Data

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.
Technical Paper

Uncertainty in Radius Determined by Multi-Point Curve Fits for Use in the Critical Curve Speed Formula

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.
Technical Paper

Reconstructing Vehicle Dynamics from On-Board Event Data

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.
Technical Paper

On the Directionality of Rollover Damage and Abrasions

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.
Technical Paper

Measuring and Modeling Suspensions of Passenger Vehicles

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.