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The Use of Stationary Object Radar Sensor Data from Advanced Driver Assistance Systems (ADAS) in Accident Reconstruction

机译:在事故重建中,使用高级驾驶员辅助系统(ADAS)的静止物体雷达传感器数据

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As a result of the development of Event Data Recorders (EDR) and the recent FMVSS regulation 49 CFR 563, today’s automobiles provide a limited subset of electronic data measurements of a vehicle’s state before and during a crash. Prior to this data, the only information available about the vehicle movements before or during a collision had come from physical evidence (e.g. tire marks), witnesses, aftermarket camera systems on vehicles, and ground-based cameras that were monitoring vehicle traffic or used for security surveillance. Today’s vehicles equipped with Advanced Driver Assistance Systems (ADAS) have vehicle-based sensors that measure information about the environment around a vehicle including other vehicles, pedestrians, and fixed wayside objects. Vehicles equipped with these ADAS systems use primarily radar, lidar, ultrasonic, and/or image sensors either in standalone operation or in combination to establish the range and movement of potential hazardous objects (e.g. other vehicles, poles, and pedestrians) around a vehicle. The data from these sensors is unique because it measures objective environment information surrounding a vehicle, which can play a role in reconstructing and understanding the contributing factors of an accident. As more vehicles become equipped with advanced safety systems and the requisite sensors for automated vehicles, accident investigators will need to become familiar with system functionality, the data that the sensors measure and may record, as well as the limitations of that data in order to effectively and accurately analyze a crash.This paper reviews the sensors in ADAS collision avoidance systems that may be present on current vehicles and how the data from a vehicle based radar may be used to reconstruct a collision. A radar sensor mounted on a host vehicle is experimentally evaluated using stationary objects, and a stationary and moving radar. The results demonstrate how an investigator would use the radar data to recognize a fixed object in the environment and analyze the relative position with respect to the host vehicle. The analysis of this radar data includes the limitations, accuracy, and validation of the particular radar sensor data. In addition, the authors propose in general how data from radars could be used to elucidate the location of fixed objects in the environment surrounding a vehicle for the purpose of understanding an accident.
机译:作为事件数据记录开发(EDR)和最近的FMVSS法规49 CFR 563的结果,今天的汽车前,在碰撞过程中提供车辆状态的电子数据测量的一个有限的子集。在此之前的数据,还提供了有关前或碰撞时车辆的运动的唯一信息都来自实物证据(如轮胎痕迹),证人,对车辆售后摄像系统,以及陆基相机,这些相机被监控车辆通行或用于安全监控。今天的汽车配备了先进驾驶辅助系统(ADAS)具有车载传感器,大约车辆周围环境,包括其他车辆,行人和路边的固定物体措施的信息。配备有这些ADAS系统的车辆主要使用雷达,激光雷达,超声波,和/或图像传感器或者在独立运行或组合使用以建立潜在的危险物体的范围和移动(例如其他车辆,电线杆,和行人)周围的车辆。来自这些传感器的数据是独一无二的,因为它测量周围的车辆,可以起到重建并了解事故的诱发因素作用的客观环境信息。随着越来越多的车辆开始配备有先进的安全系统和自动驾驶车辆所需的传感器,事故调查需要熟悉系统功能,数据的传感器测量,并可以在订单记录,以及这些数据的局限性,有效和准确地分析一个crash.This纸审查ADAS避撞系统的传感器,其可存在于当前的车辆,以及如何从基于车辆的雷达中的数据可以被用来重建一个碰撞。雷达传感器安装在主车辆使用静止物体的实验评价,以及固定和移动雷达。结果表明研究者将如何使用所述雷达数据以识别一个固定的物体的环境中,并且相对于主车辆分析的相对位置。这个雷达数据的分析包括的局限性,准确性及特定雷达传感器数据的验证。此外,作者一般建议从雷达数据如何被用来阐明在周边为了解事故为目的的车辆环境的固定物体的位置。

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