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This paper explores the dynamics of rollover crashes and examines factors that influence the severity of the roof-to-ground impacts that occur during these crashes. The paper first reports analysis of 12 real-world rollover accidents that were captured on video. Roll rate time histories for the vehicles in these accidents are reported and the characteristics of these curves are analyzed. Next, the paper uses analytical modeling to explore the influence that the trip phase characteristics may have on the severity of roof-to-ground impacts that occur during the roll phase. Finally, the principle of impulse and momentum is used to derive an analytical impact model for examining the mechanics of a roof-to-ground impact. This modeling is used to identify the influence of various impact conditions on the severity of a roof-to-ground impact.

This paper evaluates the use of PC-Crash simulation software for modeling the dynamics of a dolly rollover crash test. The specific test used for this research utilized a Ford sport utility vehicle and was run in accordance with SAE J2114. Scratches, gouges, tire marks and paint deposited on the test surface by the test vehicle were documented photographically and by digital survey and a diagram containing the layout of these items was created. The authors reviewed the test video to determine which part of the vehicle deposited each of these pieces of evidence. Position and orientation data for the vehicle in the test were then obtained using video analysis techniques. This data was then analyzed to determine the vehicle’s translational and rotational velocities throughout the test. Next, the test was modeled using PC-Crash.

PC-Crash™, a widely used crash analysis software package, incorporates the capability for modeling non-constant vehicle acceleration, where the acceleration rate varies with speed, weight, engine power, the degree of throttle application, and the roadway slope. The research reported here offers a validation of this capability, demonstrating that PC-Crash can be used to realistically model the build-up of a vehicle's speed under maximal acceleration. In the research reported here, PC-Crash 9.0 was used to model the full-throttle acceleration capabilities of three vehicles with automatic transmissions - a 2006 Ford Crown Victoria Police Interceptor (CVPI), a 2000 Cadillac DeVille DTS, and a 2003 Ford F150. For each vehicle, geometric dimensions, inertial properties, and engine/drivetrain parameters were obtained from a combination of manufacturer specifications, calculations, inspections of exemplar vehicles and full-scale vehicle testing.

Improvements in computer image processing and identification capability have led to programs that can rapidly perform calculations and model the three-dimensional spatial characteristics of objects simply from photographs or video frames. This process, known as structure-from-motion or image based scanning, is a photogrammetric technique that analyzes features of photographs or video frames from multiple angles to create dense surface models or point clouds. Concurrently, unmanned aircraft systems have gained widespread popularity due to their reliability, low-cost, and relative ease of use. These aircraft systems allow for the capture of video or still photographic footage of subjects from unique perspectives. This paper explores the efficacy of using a point cloud created from unmanned aerial vehicle video footage with traditional single-image photogrammetry methods to recreate physical evidence at a crash scene.

This paper describes, demonstrates and validates a method for incorporating the effects of restitution into crush analysis. The paper first defines the impact coefficient of restitution in a manner consistent with the assumptions of crush analysis. Second, modified equations of crush analysis are presented that incorporate this coefficient of restitution. Next, the paper develops equations that model restitution response on a vehicle-specific basis. These equations utilize physically meaningful empirical constants and thus improve on restitution modeling equations already in the literature of accident reconstruction. Finally, the paper presents analysis of four vehicle-to-vehicle crash tests, demonstrating that the application of the restitution model derived in this paper results in crush analysis yielding more accurate ΔV calculations.

PC-Crash is a vehicular accident simulation software that is widely used by the accident reconstruction community. The goal of this article is to review the prior literature that has addressed the capabilities of PC-Crash and its accuracy and reliability for various applications (planar collisions, rollovers, and human motion). In addition, this article aims to add additional analysis of the capabilities of PC-Crash for simulating planar collisions and rollovers. Simulation analysis of five planar collisions originally reported and analyzed by Bailey [2000] are reexamined. For all five of these collisions, simulations were obtained with the actual impact speeds that exhibited excellent visual agreement with the physical evidence. These simulations demonstrate that, for each case, the PC-Crash software had the ability to generate a simulation that matched the actual impact speeds and the known physical evidence.

Crash severity is quantified by the change in velocity experienced by a vehicle during an impact along with the time duration over which that change in velocity occurs. Since the values of the input parameters for calculating the change in velocity are not known exactly, there is uncertainty associated with the calculated change in velocity. Accurate evaluation of the crash severity will, therefore, include analysis of the effect that uncertainties in the values of the input parameters have on the calculated change in velocity. Monte Carlo simulation, a statistical technique, enables the reconstructionist to evaluate the effect of uncertainty on the analysis of crash severity. Use of the Monte Carlo simulation technique is beneficial since a reconstructionist can enter a range of values for each input parameter.

When a motorcycle collides with a passenger vehicle, the impact can cause a change in the translational and rotational velocities of the struck vehicle. If these velocity changes, or the magnitude of the translation and rotation of the struck vehicle can be quantified, then these can potentially be used to calculate the impact speed of the motorcycle. There are several methods that could be used for this analysis. The most general and comprehensive solution will be to use one of the widely-accepted accident reconstruction simulation programs - PC-Crash, HVE (the EDSMAC4 or SIMON modules), Virtual CRASH, or VCRware. However, these simulation programs can be time-consuming to apply and not everyone has access to them. It would be useful to have simple formulas for obtaining a reasonable estimate of the motorcycle impact speed based on the observed post-impact translation and rotation of the struck vehicle.

This paper validates the single-track vehicle driver model available in PC-Crash simulation software. The model is tested, and its limitations are described. The introduction of this model eliminated prior limitations that PC-Crash had for simulating motorcycle motion. Within PC-Crash, a user-defined path can be established for a motorcycle, and the software will generate motion consistent with the user-defined path (within the limits of friction and stability) and calculate the motorcycle lean (roll) generated by following that path at the prescribed speed, braking, or acceleration levels. In this study, the model was first examined for a simple scenario in which a motorcycle traversed a pre-defined curve at several speeds. This resulted in the conclusion that the single-track driver model in PC-Crash yielded motorcycle lean angles consistent with the standard, simple lean angle formula widely available in the literature.