Detecting the intention of drivers is an essential task in self-driving, necessary to anticipate sudden events like lane changes and stops. Turn signals and emergency flashers communicate such intentions, providing seconds of potentially critical reaction time. In this paper, we propose to detect these signals in video sequences by using a deep neural network that reasons about both spatial and temporal information. Our experiments on more than a million frames show high per-frame accuracy in very challenging scenarios.
翻译:检测驾驶员的意图是自我驾驶的一项基本任务,这是预测诸如车道改变和停车等突发事件所必需的。 转换信号和紧急闪电器可以传达这种意图, 提供几秒钟潜在关键反应时间。 在本文中, 我们提议使用一个深层神经网络来检测视频序列中的这些信号, 它既说明空间信息,也说明时间信息。 我们在100多万个框架上的实验显示,在非常具有挑战性的情况下,每个框架的精确度很高。