Browse Topic: Safety testing and procedures
Theory and principles of occupant protection for automobiles in rear-end collisions have experienced significant evolution over the decades. Performance of the seatback, specifically the stiffness of the structure, during such a collision has been a subject of particular interest and debate among design engineers, accident reconstruction experts, critics, etc. The majority of current seat designs rely on plastic deformation of the seatback structure to protect the occupant from the dynamics of the crash. In attempt to highlight and provide background information for understanding this subject, this work highlights significant events, research, and publications over the past five decades to illustrate how this subject, automobile design, government regulation and public opinion has evolved. It is observed that technology and design for improving rear-impact protection has received less attention than collisions of other principal directions of force. The different types of
Reproducing driving scenarios involving near-collisions and collisions in a simulator can be useful in the development and testing of autonomous vehicles, as it provides a safe environment to explore detailed vehicular behavior during these critical events. CARLA, an open-source driving simulator, has been widely used for reproducing driving scenarios. CARLA allows for both manual control and traffic manager control (the module that controls vehicles in autopilot manner in the simulation). However, current versions of CARLA are limited to setting the start and destination points for vehicles that are controlled by traffic manager, and are unable to replay precise waypoint paths that are collected from real-world collision and near-collision scenarios, due to the fact that the collision-free pathfinding modules are built into the system. This paper presents an extension to CARLA’s source code, enabling the replay of exact vehicle trajectories, irrespective of safety implications
As the high-quality development of the new energy vehicle (NEV) and traction battery industries, the safety of traction batteries has become a global focus. Typically mounted at the bottom of NEVs, traction battery systems are particularly vulnerable to mechanical damage caused by bottom impacts, posing serious safety risks. This study investigates the damage sustained by NEV traction battery systems during bottom impact collisions, using computer tomography analysis to detail the damage mechanisms. The findings provide valuable data to enhance the safety and protective performance of traction batteries under such scenarios.
A total of 148 tests were conducted to evaluate the Forward Collision Warning (FCW) and Automatic Emergency Braking (AEB) systems in five different Tesla Model 3 vehicles between model years 2018 and 2020 across four calendar years. These tests involved stationary vehicle targets, including a foam Stationary Vehicle Target (SVT), a Deformable Stationary Vehicle Target (DSVT), a live vehicle with brake lights, and a SoftCar360 designed for high-speed impact tests. The evaluations were conducted at speeds of 35, 50, 60, 65, 70, 75, and 80 miles per hour (mph) during both daytime and nighttime conditions and utilized early and medium FCW settings. These settings, part of Tesla's Collision Avoidance AssistTM, modify object detection alerts and the timing of visual and auditory warnings issued to drivers. The 2018 to 2020 vehicles initially utilized cameras, radar and ultrasonic sensors (USS) for object detection. Tesla updated their Autoilot software and detection algorithms to a vision
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