Department of City and Regional Planning, University of North Carolina, Chapel Hill, North Carolina.
Highway Safety Research Center, University of North Carolina, Chapel Hill, North Carolina.
Am J Prev Med. 2019 Jan;56(1):1-7. doi: 10.1016/j.amepre.2018.06.024. Epub 2018 Oct 15.
U.S. pedestrian fatalities have risen recently, even as vehicles are equipped with increasingly sophisticated safety and crash avoidance technology. Many experts expect that advances in automated vehicle technology will reduce pedestrian fatalities substantially through eliminating crashes caused by human error. This paper investigates automated vehicles' potential for reducing pedestrian fatalities by analyzing nearly 5,000 pedestrian fatalities recorded in 2015 in the Fatality Analysis Reporting System, virtually reconstructing them under a hypothetical scenario that replaces involved vehicles with automated versions equipped with state-of-the-art (as of December 2017) sensor technology.
This research involved the following activities: (1) establish functional ranges of state-of-the-art pedestrian sensor technologies, (2) use data from the Fatality Analysis Reporting System to identify pedestrian fatalities recorded in each state in the U.S. and District of Columbia in 2015, and (3) assess the maximum numbers of pedestrian fatalities that could have been avoided had involved vehicles been replaced with autonomous versions equipped with the described sensors. The research was conducted from July to December 2017.
Sensors' abilities to detect pedestrians in advance of fatal collisions vary from <30% to >90% of fatalities. Combining sensor technologies offers the greatest potential for eliminating fatalities, but may be unrealistically expensive. Furthermore, whereas initial deployment of automated vehicles will likely be restricted to freeways and select urban areas, non-freeway streets and rural settings account for a substantial share of pedestrian fatalities.
Although technologies are being developed for automated vehicles to successfully detect pedestrians in advance of most fatal collisions, the current costs and operating conditions of those technologies substantially decrease the potential for automated vehicles to radically reduce pedestrian fatalities in the short term.
最近，美国行人死亡人数有所上升，尽管车辆配备了越来越先进的安全和防撞技术。许多专家预计，自动驾驶汽车技术的进步将通过消除人为失误造成的事故，大幅减少行人死亡人数。本文通过分析 2015 年在伤亡分析报告系统中记录的近 5000 起行人死亡事故，假设用配备最先进（截至 2017 年 12 月）传感器技术的自动驾驶版本替换所涉及的车辆，来研究自动驾驶汽车减少行人死亡的潜力。
本研究包括以下活动：（1）确定最先进行人传感器技术的功能范围，（2）使用伤亡分析报告系统的数据，确定 2015 年美国各州和哥伦比亚特区记录的行人死亡人数，（3）评估如果用配备描述传感器的自动驾驶版本替换所涉及的车辆，可能避免的行人死亡人数。研究于 2017 年 7 月至 12 月进行。
传感器在致命碰撞前提前检测行人的能力从 <30%到 >90%的致命事故不等。传感器技术的结合提供了消除致命事故的最大潜力，但可能不切实际地昂贵。此外，尽管自动驾驶汽车的初步部署可能仅限于高速公路和特定城市地区，但非高速公路和农村地区也占行人死亡的很大比例。
尽管正在为自动驾驶汽车开发成功地在大多数致命碰撞前提前检测行人的技术，但这些技术的当前成本和操作条件大大降低了自动驾驶汽车在短期内大幅减少行人死亡人数的潜力。
