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Photogrammetry is a commonly used and accepted technique within the field of accident reconstruction for taking measurements from photographs. Previous work has shown the accuracy of optimized close-range photogrammetry techniques to be within 2 mm compared to other high accuracy measurement techniques when using a known calibrated camera. This research focuses on the use of inverse camera close-range photogrammetry, where photographs from an unknown camera are used to model a vehicle. Photogrammetry is a measurement technique that utilizes triangulation to take measurements from photographs. The measurements are dependent on the geometry of the camera, such as the sensor size, focal length, lens type, etc. Three types of cameras were tested for accuracy; a high-end commercial camera, a point and shoot camera, and a cell phone camera.

In previous work, Reuss [1] studied the cycle-to-cycle variation in the large-scale velocity structures of high and low-swirl in-cylinder flows of an IC engine. The vector flow fields were obtained from PIV measurements in a two-valve, pancake-shaped, Transparent Combustion Chamber (TCC) engine. In this study, the Reynolds-decomposed turbulence properties such as kinetic energy, length scales, and dissipation rate were directly measured for the two cases. The results demonstrate that, at TDC compression, the low-swirl flow is dominated by turbulence at the largest scales, whereas the high-swirl flow has a considerably lower turbulence Reynolds number. The dissipation rate and length scale calculated from mixing-length theory greatly exceeded the dissipation computed from the 2-D velocity-gradients and integral-length scales computed from the autocorrelation, respectively.

Several GoPro camera models contain Global Positioning System (GPS), accelerometer, and gyroscope instrumentation and are capable of measuring and recording position, velocity, acceleration, and inertial data. This study evaluates the accuracy of data obtained from GoPro cameras through a series of controlled tests. A test vehicle was instrumented with a Racelogic VBOX data acquisition unit as well as various generations of GoPro camera units equipped with GPS capability and driven on a road course. The raw data collected with the GoPro cameras and the translations of this data provided by the GoPro Quik desktop software application were compared to data collected with the validated VBOX data acquisition unit. The results demonstrated that position, velocity, and acceleration data recorded with GoPro cameras is consistent with VBOX data and is useful for applications related to accident reconstruction.

Understanding when an object enters into the headlamp projection from a vehicle is useful to assist the driver in detecting the object in dark or nighttime conditions. Understanding the specific illumination pattern of a vehicle headlamp beam is useful for the evaluation of nighttime visibility issues in accident reconstruction. Determining when an object entered in the headlamp beam at a specific illuminance may be of particular importance to driver avoidance capabilities. Headlamp illumination patterns may be unique to each vehicle make and model. In this study, the headlamp illumination patterns of multiple vehicles were mapped, and the measured illumination distances were compared with empirical predications. In general, individual headlamp illumination distances fell within the range of minimum and maximum empirical predictions.

Understanding the specific illumination pattern of a vehicle headlamp beam is useful for the evaluation of nighttime visibility issues in accident reconstruction. There are several challenges associated with traditional headlamp mapping techniques, including that mapping must be conducted in darkness, the mapping location topography may not be level or flat, maintaining a measurement grid is difficult to accomplish in the field, data acquisition requires multiple individuals, and it is generally very time consuming. Traditional techniques require the surrounding surface to be permanently marked in the evening in order to allow for future data collection of the mapped points in daylight conditions. The methodology presented here alleviates some of these challenges through real-time data collection and by accounting for topographical differences, which eliminates the requirement that mapping be conducted on a level or flat surface, and it reduces the number of required participants.

There is a limited amount of data currently available on the acceleration and braking performances of school buses. This paper analyzes the braking performance of various Type A and Type C school buses with hydraulic and air brakes. The effect of ABS and Non-ABS systems as well as driver experience is discussed. A comparison with passenger car braking performance is presented. The acceleration of a school bus is also presented. Evaluations of “normal” and “rapid” accelerations are presented for Type A and Type B buses. A comparison with commonly used acceleration values for various vehicles is presented.

A and B stiffness coefficients to model the frontal stiffness of vehicles is a commonly used and accepted technique within the field of collision reconstruction. Methods for calculating stiffness coefficients rely upon examining the residual crush of a vehicle involved in a crash test. When vehicles are involved in a collision, portions of the crushed vehicle structures rebound from their maximum dynamic crush position. Once the vehicle structures have finished rebounding, the remaining damage is called the residual crush. A problem can arise when the plastic bumper cover rebounds more than the vehicle's structural components, resulting in an air gap between the structural components and the plastic bumper cover. Most modern New Car Assessment Program (NCAP) tests quantify crush in the test reports based on the deformed location of the plastic bumper cover and not the structural components behind the plastic bumper cover. This results in an underreporting of the actual residual crush.