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Hands Off the Wheel in Autonomous Vehicles?: A Systems Perspective on over a Million Miles of Field Data

机译:会自动驾驶无人驾驶汽车吗?:百万英里现场数据的系统透视

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Autonomous vehicle (AV) technology is rapidly becoming a reality on U.S. roads, offering the promise of improvements in traffic management, safety, and the comfort and efficiency of vehicular travel. The California Department of Motor Vehicles (DMV) reports that between 2014 and 2017, manufacturers tested 144 AVs, driving a cumulative 1,116,605 autonomous miles, and reported 5,328 disengagements and 42 accidents involving AVs on public roads. This paper investigates the causes, dynamics, and impacts of such AV failures by analyzing disengagement and accident reports obtained from public DMV databases. We draw several conclusions. For example, we find that autonomous vehicles are 15 - 4000Ã- worse than human drivers for accidents per cumulative mile driven; that drivers of AVs need to be as alert as drivers of non-AVs; and that the AVs' machine-learning-based systems for perception and decision-and-control are the primary cause of 64% of all disengagements.
机译:自主车辆(AV)技术在美国道路上正迅速成为现实,并有望改善交通管理,安全性以及车辆出行的舒适度和效率。加州汽车部(DMV)报告称,2014年至2017年期间,制造商测试了144辆自动驾驶汽车,累计行驶了1,116,605英里的自动行驶里程,并报告了5,328例脱离接合和42例涉及公共道路上的自动驾驶汽车的事故。本文通过分析从公共DMV数据库获得的脱离接触和事故报告来调查此类AV故障的原因,动态和影响。我们得出一些结论。例如,我们发现,自动驾驶汽车每行驶一英里所发生的事故要比人类驾驶员差15-4000埃; AV的驱动程序需要与非AV的驱动程序一样警惕; AV的基于机器学习的感知,决策和控制系统是导致所有脱离的64%的主要原因。

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