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Analysis of pedestrian-to-vehicle collisions can be complex due to the nature of the interaction and the physics involved. The scarcity of evidence like video evidence (from CCTV or dashcams), data from the vehicle's ECU, witness accounts, and physical evidence such as tyre marks, complicates the analysis of these incidents. In cases with limited evidence, current forensic methods often rely on prolonged inquiry processes or computationally intensive simulations. Without adequate data, accurately estimating pedestrian kinematics and addressing hit-and-run scenarios becomes challenging. This research provides an alternative approach to enhancing pedestrian forensic analysis based on machine learning (ML) algorithms trained on over 3000 multi-body computer simulations with a diverse set of vehicle profiles and pedestrian anthropometries.

Sloped medians provide a run-off area for errant vehicles so that they can be safely stopped off-road with or without barriers placed in the sloped median. However, in order to optimize the design of sloped medians and the containment barriers, it is essential to accurately model the behavior of vehicles on such sloped terrain surfaces. In this study, models of a vehicle fleet comprising a small sedan and a pickup truck and sloped terrain surface are developed in CarSim™ to simulate errant vehicle behavior on sloped median. Full-scale crash tests were conducted using the vehicle fleet driven across a 9.754 meters wide median with a 6:1 slope at speeds ranging from 30 to 70 km/h. Measured data such as the lateral accelerations of the vehicle as well as chassis rotations (roll and pitch) were synchronized with the vehicle motion obtained from the video data.

The aims of this study are to investigate the responses of a Hybrid III dummy and a human body model in rollover crashes of an SUV, and to assess the effect of seat belts on occupant kinematics in rollover events. A SAEJ2114 rollover test of a 1994 Ford Explorer for two front row dummies with an inflatable tubular structure (ITS) is reconstructed and validated in MADYMO. By removing the ITS, the simulations of the Hybrid III dummy occupants with and without seat belts are obtained. By replacing the dummy models with human body models, with and without seat belts, two other combinations are also modelled. The kinematics and injury risks of two kinds of occupant models are compared and evaluated. Significant differences exist in the motions, and injury levels of the dummies and human body models with and without seat belts. Seat belts can significantly mitigate against occupant ejection.

In recent years in the United Kingdom, dual-fuelled vehicles incorporating Liquid Petroleum Gas (LPG) have become more prevalent, as there are the perceived benefits of reduced fuelling costs, whilst also reducing the harmful emissions that effect air quality and climate change. In 2001, over 75,000 vehicles were registered as being powered by LPG and it is estimated that nearly 250,000 conversions were made to UK cars by the end of 2004. It is considered that the world population of such vehicles is in the order of 5 million vehicles, 2 million of which are being driven within EU countries.1 This paper will therefore examine the incidence of car fires in the area covered by Hereford and Worcester Fire and Rescue Service (HWFRS) in the UK. The data was used to establish the travel time for fire pumps to such incidents, the amount of time those units were detained at the scene and the possible cause of the fires themselves.

Millimetre wave radar sensors are being actively developed for automotive applications including Intelligent Cruise Control (ICC), Collision Warning (CW), and Collision Avoidance (CA). Knowledge of the road geometry is of fundamental importance to these future intelligent automotive systems. The interest in such systems is evidenced by manufacturers now starting to incorporate radars in production luxury vehicles. Determination of the road geometry, day and night, under all weather conditions, is a challenging problem requiring both fundamental research and systems studies. Current automotive radar systems rely heavily on the use of extrapolating yaw rate data generated within the vehicle to produce a prediction of the path of the road ahead. This use of historical data is only satisfactory if the road trajectory is uniform. Sudden discontinuities in the path, such as bends, cause this method of path prediction to produce significant errors.

The effects of child safety seats have been well documented in the medical literature. Scattered throughout the medical literature are individual case reports of cervical injury to children restrained in child restraint systems. A review of the literature is provided identifying previous documented cases. The authors also provide new case details of children with cervical spine injury without head contact. An overview of the growth of the infant and specific details in the cervical spine that may contribute to significant cervical injury without head impact is presented.

Crash injury reduction via lap-shoulder belt use has been well documented. As any interior car component, lap-shoulder belts may be related to injury in certain crashes. Relatively unknown is the fact that cervical fractures or fracture-dislocations to restrained front seat occupants where, in the crash, no head contact was evidenced by both medical records and car inspection. An extensive review of the available world's literature on car crash injuries revealed more than 100 such cases. A review of the NASS 80-88 was also conducted, revealing more examples. Cases from the author's own files are also detailed.