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Accident scene data obtained from photographs and videos are vital to the analysis performed during accident reconstruction. They allow forensic analysts to precisely determine the orientation and location of evidence. For that reason, the term digital evidence was adopted and is commonly used by forensic analysts in conjunction with retro-projection methods as an aid to reconstruct the events leading up to the incident in question. Photogrammetry is a retro-projection method commonly used by analysts to match scene photographs with calibrated control points obtained from three-dimensional point cloud data collected at the subject accident site and visualized on the accident scene images. From this merger, the photographs allow for the determination of the point at which the camera was positioned that took the subject image. In general, the point cloud data allows for increased accuracy during the photogrammetry process.

Fleet management companies have implemented tracking devices in their vehicles that employ Global Positioning Systems (GPS) in near real time for optimizing fuel consumption, smart routes, and for monitoring driving behavior. For this purpose, Geotab Inc. has developed the OBD-II connected Geotab GO device. These devices are capable of recording vehicle position and speed data using GPS. The present study seeks to validate and compare Geotab recorded data to data collected from a VBOX 3i RTK DGPS; this instrumentation will provide a reliable reference for vehicle position and speed. Additional data logging characteristics such as LTE connectivity, Geotab’s proprietary curve logging algorithm, near-real-time vehicle data, and speed interpolation were analyzed. This study considered two Geotab models, the GO8 and GO9. Both devices were connected in parallel using two sets of two-way splitters connected to the test vehicle’s OBD-II port.

Tesla Motors vehicles utilize a regenerative braking system to increase mileage per charge. The system is designed to convert the vehicles’ kinetic energy during coast-down into electrical potential energy by using rotational wheel motion to charge the batteries, resulting in moderate deceleration. During this coast-down, the system will activate the brake lights to notify following vehicles of deceleration. The goals of this study were to analyze and quantify the regenerative braking behavior of the Tesla Model 3, S, and X, as well as the timing and activation criteria for the brake lights during the coast-down state. A total of seven Tesla vehicles (two Model 3, three Model S and two Model X) were tested in both Standard and Low regenerative braking modes. All three Tesla models exhibited similar three-phase behavior: an initial ramp-up phase, a steady-state phase, and a non-linear ramp-down phase at low road speeds. Phase 1 was less than one second in length.

Three fully electric motorcycles were tested and analyzed for acceleration, braking, and regenerative coast-down deceleration. A Zero DSR, BMW C-Evolution, and a Harley-Davidson LiveWire underwent each of the following test series. The first test series consisted of accelerating the electric motorcycles from a stop. For the second test series, the motorcycles were decelerated by using three different brake applications: front and rear brake application, front-only brake application, and rear-only brake application. For the third test series, regenerative coast-down deceleration was tested at different ride mode configurations. Regenerative braking systems are designed to convert the vehicles’ kinetic energy into electrical potential energy during the vehicles’ coast-down phase, resulting in a moderate deceleration. In addition to testing the vehicles’ deceleration during its’ regenerative coast-down phase, brake light activation delay relative to throttle roll-off was analyzed.

Every day in the United States, an average of approximately two cyclists die in bicycle accidents. Sometimes, forensic engineers are asked to reconstruct these accidents. These cyclists may use bicycle GPS devices to record important data, which they use to monitor their riding activities. By analyzing this data, many questions can be answered regarding various parameters such as speed, position, and riding behavior of the bicyclist. The goal of this study was to analyze the accuracy of the GPS position and speed data. For this study, four different bicycle GPS devices (one of which was paired with a magnetometer Garmin Bicycle Speed Sensor), a GoPro camera equipped with GPS, and a smartphone recording to Strava, were mounted on a bicycle. The bicycle was ridden in an approximately straight line (back and forth), and then around a building, to measure positional and speed accuracy.

The objective of this study was to analyze the validity of airbag control module data in semi-trailer rear underride collisions. These impacts involve unusual collision dynamics, including long crash pulses and minimal bumper engagement [1]. For this study, publicly available data from 16 semi-trailer underride guard crash tests performed by the Insurance Institute for Highway Safety (IIHS) were used to form conclusions about the accuracy of General Motors airbag control module (ACM) delta-V (ΔV) data in a semi-trailer rear underride scenario. These tests all utilized a 2009 or 2010 Chevrolet Malibu impacting a stationary 48’ or 53’ semi-trailer at a speed of 35 mph. Nine tests were fully overlapped collisions, six were 30% overlapped, and one was 50% overlapped [2]. The IIHS test vehicles were equipped with calibrated 10000 Hz accelerometer units. Event Data Recorder (EDR) data imaged post-accident from the test vehicles were compared to the reference IIHS data.

PC-Crash is an accident reconstruction program that enables the user to analyze vehicle collision dynamics and trajectory models. This research paper presents the utilization of PC-Crash to analyze motorcycle slide-to-stop dynamics. For this study, existing motorcycle slide-to-stop data from SAE 2019-01-0426 will be simulated and analyzed in PC-Crash. The selected dataset consists of three motorcycles: a 2002 Kawasaki ZRX-1200R, a 2006 Yamaha YZF-R6, and a 2013 Ninja EX300. Six of the thirteen slide-to-stop tests collected by Fatzinger [1] were simulated and analyzed in PC-Crash. The motorcycle initial ground contact speeds range from 37-52 mph. Parameters such as vehicle weight, sliding friction factor, motorcycle sliding trajectory, and yaw trajectory will be accounted for in each PC-Crash simulation. All tests were simulated using a 2D and 3D motorcycle model in PC-Crash.

PC-Crash is an accident reconstruction program allowing the user to perform simulations with multibody objects that collide or interact with 3D vehicle mesh models. The multibody systems can be a pedestrian, a motorcycle, or a motorcycle with a rider. The multibody systems are comprised of individual rigid bodies connected by joints. The bodies can be of various size and stiffness along with varying coefficients of friction and restitution. Additionally, the joints can be tailored to define pivot types and range of motion. The current motorcycle models in PC-Crash are generic and do not resemble a sport bike type motorcycle. They are only globally scalable such that you cannot adjust length, width, or height independently. However, the user can adjust each body and/or joint individually as needed. A model was created that resembled a modern sport bike motorcycle. In addition, a multibody rider was mounted on the motorcycle in a typical sport bike riding position.