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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.

Many motorcycle crashes involve the motorcycle capsizing, impacting the ground, and sliding on the road surface. When performing speed calculations, the energy or speed loss for the ground impact and sliding phases may need to be calculated. To perform these calculations, the reconstructionist will typically determine the slide distance based on the physical evidence and then apply a range of decelerations over that distance based on test data in the literature. Decelerations can be selected for motorcycles with similar characteristics (crash bars, panniers, fairings, etc.) sliding on similar surfaces (asphalt, concrete, dirt, gravel, etc.). This approach is adequate but sometimes results in a wide range due to the variability in reported decelerations in prior studies. It could be helpful to narrow the likely range of decelerations, and thus, the speed range.

Accident reconstruction utilizes principles of physics and empirical data to analyze the physical, electronic, video, audio, and testimonial evidence from a crash, to determine how and why the crash occurred, how the crash could have been avoided, or to determine whose description of the crash is most accurate. This process draws together aspects of mathematics, physics, engineering, materials science, human factors, and psychology, and combines analytical models with empirical test data. Different types of crashes produce different types of evidence and call for different analysis methods. Still, the basic philosophical approach of the reconstructionist is the same from crash type to crash type, as are the physical principles that are brought to bear on the analysis.

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 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.

In a recent National Highway Traffic Safety Administration (NHTSA) report, about one out of every 7 fatalities on the road involved a motorcycle. Itis clear that motorcyclists are more vulnerable and much more likely to be injured or killed in a crash than are passengers in a car accident. Motorcycle Accident Reconstruction purposefully pulls together as much of the relevant accident reconstruction literature and science as possible to present definitive literature that meets the needs of the crash reconstruction industry. The reader will learn to analyze physical evidence, understand what it means, and how to incorporate math and physics into an investigation. Topics featured in this book include: Case studies utilizing event data recorder data Photogrammetry analysis Determining motorcycle speed at the time of an accident The book provides a unique roadmap for the motorcycle accident reconstructionist user.

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.

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.

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.

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.

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.

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.

Previous work demonstrated that the orientation of tire mark striations can be used to infer the braking actions of the driver [1]. An equation that related tire mark striation angle to longitudinal tire slip, the mathematical definition of braking, was presented. This equation can be used to quantify the driver’s braking input based on the physical evidence. Braking input levels will affect the speed of a yawing vehicle and quantifying the amount of braking can increase the accuracy of a speed analysis. When using this technique in practice, it is helpful to understand the sensitivity and uncertainties of the equation. The sensitivity and uncertainty of the equation are explored and presented in this study. The results help to formulate guidelines for the practical application of the method and expected accuracy under specified conditions. A case study is included that demonstrates the analysis of tire mark striations deposited during a real-world accident.

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.

Several sources report simple equations for calculating the lean angle required for a motorcycle and rider to traverse a curved path at a particular speed. These equations utilize several assumptions that reconstructionists using them should consider. First, they assume that the motorcycle is traveling a steady speed. Second, they assume that the motorcycle and its rider lean to the same lean angle. Finally, they assume that the motorcycle tires have no width, such that the portion of the tires contacting the roadway does not change or move as the motorcycle and rider lean. This study reports physical testing that the authors conducted with motorcycles traversing curved paths to examine the net effect of these assumptions on the accuracy of the basic formulas for motorcycle lean angle. We concluded that the basic lean angle formulas consistently underestimate the lean angle of the motorcycle as it traverses a particular curved path.

In a 2012 paper, Brach, Brach, and Louderback (BBL) investigated the uncertainty that arises in calculating the change in velocity and crush energy with the use of the CRASH3 equations (2012-01-0608). They concluded that the uncertainty in these values caused by variations in the stiffness coefficients significantly outweighed the uncertainty caused by variations in the crush measurements. This paper presents a revised analysis of the data that BBL analyzed and further assesses the level of uncertainty that arises in CRASH3 calculations. While the findings of this study do not invalidate BBL's ultimate conclusion, the methodology utilized in this paper incorporated two changes to BBL's methodology. First, in analyzing the crash test data for several vehicles, a systematic error that is sometimes present in the reported crush measurements was accounted for and corrected.

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.

This paper reports a method for analyzing data from a DriveCam unit to determine impact speeds and velocity changes in vehicle-to-vehicle impacts. A DriveCam unit is an aftermarket, in-vehicle, event-triggered video and data recorder. When the unit senses accelerations over a preset threshold, an event is triggered and the unit records video from two camera views, accelerations along three directions, and the vehicle speed with a GPS sensor. In conducting the research reported in this paper, the authors ran four front-to-rear crash tests with two DriveCam equipped vehicles. For each test, the front of the bullet vehicle impacted the rear of the stationary target vehicle. Each of the test vehicles was impacted in the rear twice - once at a speed of around 10 mph and again at a speed around 25 mph. The accuracy of the DriveCam acceleration data was assessed by comparing it to the data from other in-vehicle instrumentation.

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.