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Accident reconstructionists routinely rely on computer software to perform analyses. While there are a variety of software packages available to accident reconstructionists, many rely on custom spreadsheet-based applications for their analyses. Purchased packages provide an improved interface and the ability to produce sophisticated animations of vehicle motion but can be cost prohibitive. Pycrash is a free, open-source Python-based software package that, in its current state, can perform basic accident reconstruction calculations, automate data analyses, simulate single vehicle motion and, perform impulse-momentum based analyses of vehicle collisions. In this paper, the current capabilities of Pycrash are illustrated and its accuracy is assessed using matching PC-Crash simulations performed using PC-Crash.

This paper introduces a method for calculating vehicle speed and uncertainty range in speed from video footage. The method considers uncertainty in two areas; the uncertainty in locating the vehicle’s position and the uncertainty in time interval between them. An abacus style timing light was built to determine the frame time and uncertainty of time between frames of three different cameras. The first camera had a constant frame rate, the second camera had minor frame rate variability and the third had more significant frame rate variability. Video of an instrumented vehicle traveling at different, but known, speeds was recorded by all three cameras. Photogrammetry was conducted to determine a best fit for the vehicle positions. Deviation from that best fit position that still produced an acceptable range was also explored. Video metadata reported by iNPUT-ACE and Mediainfo was incorporated into the study.

According to the National Highway Traffic Safety Administration, “of the nearly 9.1 million passenger car, SUV, pickup and van crashes in 2010, only 2.1% involved a rollover. However, rollovers accounted for nearly 35% of all deaths from passenger vehicle crashes. In 2010 alone, more than 7,600 people died in rollover crashes.” Rollover accidents continue to be a leading contributor of vehicle deaths. While this continues to be true, it is pertinent to understand the entire crash process. Each stage of the accident provides valuable insight into the application of reconstruction methodologies. Rollover Accident Reconstruction focuses on tripped, single vehicle rollover crashes that terminate without striking a fixed object.

Tire mark striations are discussed often in the literature pertaining to accident reconstruction. The discussions in the literature contain many consistencies, but also contain disagreements. In this article, the literature is first summarized, and then the differences in the mechanism in which striations are deposited and interpretation of this evidence are explored. In previous work, it was demonstrated that the specific characteristics of tire mark striations offer a glimpse into the steering and driving actions of the driver. An equation was developed that relates longitudinal tire slip (braking) to the angle of tire mark striations [1]. The longitudinal slip equation was derived from the classic equation for tire slip and also geometrically. In this study, the equation for longitudinal slip is re-derived from equations that model tire forces.

Accurately reconstructing the speed of a yawing and braking vehicle requires an estimate of the varying rates at which the vehicle decelerated. This paper explores the accuracy of several approaches to making this calculation. The first approach uses the Bakker-Nyborg-Pacejka (BNP) tire force model in conjunction with the Nicolas-Comstock-Brach (NCB) combined tire force equations to calculate a yawing and braking vehicle's deceleration rate. Application of this model in a crash reconstruction context will typically require the use of generic tire model parameters, and so, the research in this paper explored the accuracy of using such generic parameters. The paper then examines a simpler equation for calculating a yawing and braking vehicle's deceleration rate which was proposed by Martinez and Schlueter in a 1996 paper. It is demonstrated that this equation exhibits physically unrealistic behavior that precludes it from being used to accurately determine a vehicle's deceleration rate.

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.

The goal of this paper is to advance rollover crash reconstruction techniques beyond the assumption typically made that a rolling vehicle decelerates at a constant rate. The paper presents and applies a planar vehicle-to-ground impact model to explore the manner in which a vehicle’s deceleration rate would be expected to vary over the course of a rollover. Based on this analysis, several possible variable deceleration rate profile shapes are then suggested for rollover crash reconstruction. Then, two rollover crash tests are analyzed to determine the extent to which these suggested variable deceleration rate profiles can be expected to yield accurate reconstructions of the translational and angular velocity histories for actual rollovers. Overall, each of the suggested variable deceleration rate profiles represented a significant improvement over using a constant deceleration rate.

This paper explores the accuracy of a planar, impulse-momentum impact model in representing the dynamics of three vehicle-to-ground impacts that occurred during a SAE J2114 dolly rollover test. The impacts were analyzed, first, using video analysis techniques to obtain the actual velocity conditions, accelerations, impact force components and the energy loss for each of the impacts. Next, these same impacts were analyzed using the known initial velocity conditions and the subject impact model. The equations of this impact model yielded calculated values for the velocity changes and energy loss for each impact. These calculated results were then compared to the actual dynamics data from the video analysis of the impacts to determine the accuracy of the impact model results. For all three vehicle-to-ground impacts considered in this study, the impact model results for the velocity changes and energy loss showed excellent agreement with the video analysis results for these parameters.

This paper explores the influence of the impact conditions on the dynamics and the severity of rollover crashes. Causal connections are sought between the impact conditions and the crash attributes to which they lead. The paper begins by extending previously presented equations that describe the dynamics of an idealized vehicle-to-ground impact. It then considers the behavior of these equations under a variety of impact conditions that occur during real-world rollovers. Specifically, the equations of this impact model are used to explore the ways in which and the extent to which rollover dynamics and severity are influenced by the following factors: (1) the vehicle's shape and its orientation at impact, (2) its weight, center-of-mass location, and roll moment of inertia, (3) its translational speed, (4) its downward velocity, and (5) its roll velocity. Throughout this discussion, data from real-world and staged rollover crashes is used to give the parameter study an empirical basis.

A simple two-dimensional particle model was previously developed to calculate occupant ejection trajectories in rollover crashes. Model parameters were optimized using data from a dolly rollover test of a 1998 Ford Expedition in which five unbelted anthropomorphic test devices (ATDs) were completely ejected. In the present study, the model was further validated against a dolly rollover test of a 2004 Volvo XC90 in which three unbelted ATDs were completely ejected. The findings from the experimental testing were then compared to two real world rollover crashes with occupant ejections that were captured on video. The crashes were reconstructed by analyzing the video footage and aerial images of the crash sites. In both cases, the model was able to accurately match the observed trajectories of the ejected occupants, and the optimized model parameters were similar to the values obtained from the dolly rollover testing.

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 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.