The National Highway Traffic Safety Administration reported that more than 90% of in-road accidents in 2015 occurred purely because of drivers? errors and misjudgments, with such factors as fatigue and other sorts of distractions being the main cause of these accidents [1]. One promising solution for reducing (or even resolving) such human errors is via autonomous or computer-assisted driving systems. Autonomous vehicles (AVs) are currently being designed with the aim of reducing fatalities in accidents by being insusceptible to typical driver errors. Moreover, in addition to improved safety, autonomous systems offer many other potential benefits to society: 1) improved fuel efficiency beyond that of human driving, making driving more cost beneficial and environmentally friendly, 2) reduced commute times due to improved driving behaviors and coordination among AVs, and 3) a better driving experience for individuals with disabilities, to name a few.

中文翻译：

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深度神经网络感知模型和稳健的自动驾驶系统：缓解和改进的实用解决方案

美国国家公路交通安全管理局报告说，2015年90%以上的道路交通事故纯粹是因为司机？错误和误判，疲劳和其他类型的分心等因素是这些事故的主要原因[1]。减少（甚至解决）此类人为错误的一种有前途的解决方案是通过自主或计算机辅助驾驶系统。自动驾驶汽车 (AV) 目前的设计目的是通过不易受典型驾驶员错误的影响来减少事故中的死亡人数。此外，除了提高安全性之外，自主系统还为社会提供了许多其他潜在好处：1) 提高了人类驾驶以外的燃油效率，使驾驶更具成本效益和环保性，