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This paper investigates the dynamics of four motorcycle crashes that occurred on or near a curve (Edwards Corner) on a section of the Mulholland Highway called “The Snake.” This section of highway is located in the Santa Monica Mountains of California. All four accidents were captured on video and they each involved a high-side fall of the motorcycle and rider. This article reports a technical description and analysis of these videos in which the motion of the motorcycles and riders is quantified. To aid in the analysis, the authors mapped Edwards Corner using both a Sokkia total station and a Faro laser scanner. This mapping data enabled analysis of the videos to determine the initial speed of the motorcycles, to identify where in the curve particular rider actions occurred, to quantify the motion of the motorcycles and riders, and to characterize the roadway radius and superelevation throughout the curve.

This paper presents yaw testing of vehicles with tread removed from tires at various locations. A 2004 Chevrolet Malibu and a 2003 Ford Expedition were included in the test series. The vehicles were accelerated up to speed and a large steering input was made to induce yaw. Speed at the beginning of the tire mark evidence varied between 33 mph and 73 mph. Both vehicles were instrumented to record over the ground speed, steering angle, yaw angle and in some tests, wheel speeds. The tire marks on the roadway were surveyed and photographed. The Critical Speed Formula has long been used by accident reconstructionists for estimating a vehicle’s speed at the beginning of yaw tire marks. The method has been validated by previous researchers to calculate the speed of a vehicle with four intact tires. This research extends the Critical Speed Formula to include yawing vehicles following a tread detachment event.

Calculating the speed of a yawing and braked vehicle often requires an estimate of the vehicle deceleration. During a steering induced yaw, the rotational velocity of the vehicle will typically be small enough that it will not make up a significant portion of the vehicle’s energy. However, when a yaw is impact induced and the resulting yaw velocity is high, the rotational component of the vehicle’s kinetic energy can be significant relative to the translational component. In such cases, the rotational velocity can have a meaningful effect on the deceleration, since there is additional energy that needs dissipated and since the vehicle tires can travel a substantially different distance than the vehicle center of gravity. In addition to the effects of rotational energy on the deceleration, high yaw velocities can also cause steering angles to develop at the front tires. This too can affect the deceleration since it will influence the slip angles at the front tires.

In low speed collisions (under 15 mph) that involve a heavy truck impacting the rear of a passenger vehicle, it is likely that the front bumper of the heavy truck will override the rear bumper beam of the passenger vehicle, creating an override/underride impact configuration. There is limited data available for study when attempting to quantify vehicle damage and crash dynamics in low-speed override/underride impacts. Low speed impact tests were conducted to provide new data for passenger vehicle dynamics and damage assessment for low speed override/underride rear impacts to passenger vehicles. Three tests were conducted, with a tractor-trailer impacting three different passenger vehicles at 5 mph and 10 mph. This paper presents data from these three tests in order to expand the available data set for low speed override/underride collisions.

When reconstructing collisions involving left turning vehicles at intersections, accident reconstructionists are often required to determine the relative timing and spacing between two vehicles involved in such a collision. This time-space analysis frequently involves determining or prescribing a path and acceleration profile for the left turning vehicle. Although numerous studies have examined the straight-line acceleration of vehicles, only two studies have presented the tangential and lateral acceleration of left turning vehicles. This paper expands on the results of those limited studies and presents a methodology to automatically detect and track vehicles in a video file. The authors made observations of left turning vehicles at three intersections. Each intersection incorporated permissive green turn phases for left turning vehicles.

Previous studies have reported and validated equations for calculating the lean angle required for a motorcycle and rider to traverse a curved path at a particular speed. In 2015, Carter, Rose, and Pentecost reported physical testing with motorcycles traversing curved paths on an oval track on a pre-marked range in a relatively level parking lot. Several trends emerged in this study. First, while theoretical lean angle equations prescribe a single lean angle for a given lateral acceleration, there was considerable scatter in the real-world lean angles employed by motorcyclists for any given lateral acceleration level. Second, the actual lean angle was nearly always greater than the theoretical lean angle. This prior study was limited in that it only examined the motorcycle lean angle at the apex of the curves. The research reported here extends the previous study by examining the accuracy of the lean angle formulas throughout the curves.

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.

Collision statistics show that more than half of all pedestrian fatalities caused by vehicles occur at night. The recognition of objects at night is a crucial component in driver responses and in preventing nighttime pedestrian accidents. To investigate the root cause of this fact pattern, Richard Blackwell conducted a series of experiments in the 1950s through 1970s to evaluate whether restricted viewing time can be used as a surrogate for the imperfect information available to drivers at night. The authors build on these findings and incorporate the responses of drivers to objects in the road at night found in the SHRP-2 naturalistic database. A closed road outdoor study and an indoor study were conducted using an automatic shutter system to limit observation time to approximately ¼ of a second. Results from these limited exposure time studies showed a positive correlation to naturalistic responses, providing a validation of the time-limited exposure technique.

This paper reports testing and analysis of the braking and swerving capabilities of on-road, three-wheeled motorcycles. A three-wheeled vehicle has handling and stability characteristics that differ both from two-wheeled motorcycles and from four-wheeled vehicles. The data reported in this paper will enable accident reconstructionists to consider these different characteristics when analyzing a three-wheeled motorcycle operator’s ability to brake or swerve to avoid a crash. The testing in this study utilized two riders operating two Harley-Davidson Tri-Glide motorcycles with two wheels in the rear and one in the front. Testing was also conducted with ballast to explore the influence of passenger or cargo weight. Numerous studies have documented the braking capabilities of two-wheeled motorcycles with riders of varying skill levels and with a range of braking systems.

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.