a Virginia Tech , School of Biomedical Engineering and Sciences , Blacksburg , Virginia.
Traffic Inj Prev. 2014;15(7):753-61. doi: 10.1080/15389588.2013.871003.
The objective of active safety systems is to prevent or mitigate collisions. A critical component in the design of active safety systems is the identification of the target population for a proposed system. The target population for an active safety system is that set of crashes that a proposed system could prevent or mitigate. Target crashes have scenarios in which the sensors and algorithms would likely activate. For example, the rear-end crash scenario, where the front of one vehicle contacts another vehicle traveling in the same direction and in the same lane as the striking vehicle, is one scenario for which forward collision warning (FCW) would be most effective in mitigating or preventing. This article presents a novel set of precrash scenarios based on coded variables from NHTSA's nationally representative crash databases in the United States.
Using 4 databases (National Automotive Sampling System-General Estimates System [NASS-GES], NASS Crashworthiness Data System [NASS-CDS], Fatality Analysis Reporting System [FARS], and National Motor Vehicle Crash Causation Survey [NMVCCS]) the scenarios developed in this study can be used to quantify the number of police-reported crashes, seriously injured occupants, and fatalities that are applicable to proposed active safety systems. In this article, we use the precrash scenarios to identify the target populations for FCW, pedestrian crash avoidance systems (PCAS), lane departure warning (LDW), and vehicle-to-vehicle (V2V) or vehicle-to-infrastructure (V2I) systems. Crash scenarios were derived using precrash variables (critical event, accident type, precrash movement) present in all 4 data sources.
This study found that these active safety systems could potentially mitigate approximately 1 in 5 of all severity and serious injury crashes in the United States and 26 percent of fatal crashes. Annually, this corresponds to 1.2 million all severity, 14,353 serious injury (MAIS 3+), and 7412 fatal crashes. In addition, we provide the source code for the crash scenarios as an appendix (see online supplement) to this article so that researchers can use the crash scenarios in future research.
主动安全系统的目的是预防或减轻碰撞。主动安全系统设计的一个关键组成部分是确定拟议系统的目标人群。主动安全系统的目标人群是指拟议系统可以预防或减轻的碰撞集。目标碰撞具有传感器和算法可能激活的场景。例如，追尾碰撞场景，其中一辆车的前部与另一辆在与撞击车辆相同方向和同一车道行驶的车辆接触，是前方碰撞警告（FCW）最有效地减轻或预防的一种情况。本文提出了一组基于美国国家公路交通安全管理局（NHTSA）全国代表性碰撞数据库中编码变量的新型预碰撞场景。
使用 4 个数据库（国家汽车抽样系统-一般估计系统[NASS-GES]、NASS 碰撞数据系统[NASS-CDS]、伤亡分析报告系统[FARS]和国家机动车碰撞因果调查系统[NMVCCS]），本研究开发的场景可用于量化适用于拟议主动安全系统的警察报告碰撞、重伤乘客和死亡人数。在本文中，我们使用预碰撞场景来确定 FCW、行人防撞系统（PCAS）、车道偏离警告（LDW）和车对车（V2V）或车对基础设施（V2I）系统的目标人群。碰撞场景是使用所有 4 个数据源中存在的预碰撞变量（关键事件、事故类型、预碰撞运动）得出的。
本研究发现，这些主动安全系统可能潜在地减轻美国约五分之一的所有严重程度和严重伤害碰撞，以及 26%的致命碰撞。每年，这对应于 120 万次所有严重程度、14353 次严重伤害（MAIS 3+）和 7412 次致命碰撞。此外，我们在本文的附录（见在线补充）中提供了碰撞场景的源代码，以便研究人员在未来的研究中使用这些碰撞场景。
