Nowadays, there are outstanding strides towards a future with autonomous vehicles on our roads. While the perception of autonomous vehicles performs well under closed-set conditions, they still struggle to handle the unexpected. This survey provides an extensive overview of anomaly detection techniques based on camera, lidar, radar, multimodal and abstract object level data. We provide a systematization including detection approach, corner case level, ability for an online application, and further attributes. We outline the state-of-the-art and point out current research gaps.
翻译:目前,在建设未来道路上拥有自主车辆方面已经取得了显著进展。虽然对自主车辆的看法在封闭条件下表现良好,但它们仍然难以应对意外事件。这项调查提供了基于相机、利达尔、雷达、多式联运和抽象物体水平数据的广泛反常探测技术概览。我们提供了一个系统化方法,包括探测方法、转角案例水平、在线应用能力和其他属性。我们概述了最新技术,并指出了当前的研究差距。