Autonomous Vehicles (AVs) i.e., self-driving cars, operate in a safety critical domain, since errors in the autonomous driving software can lead to huge losses. Statistically, road intersections which are a part of the AVs operational design domain (ODD), have some of the highest accident rates. Hence, testing AVs to the limits on road intersections and assuring their safety on road intersections is pertinent, and thus the focus of this paper. We present a situation coverage-based (SitCov) AV-testing framework for the verification and validation (V&V) and safety assurance of AVs, developed in an open-source AV simulator named CARLA. The SitCov AV-testing framework focuses on vehicle-to-vehicle interaction on a road intersection under different environmental and intersection configuration situations, using situation coverage criteria for automatic test suite generation for safety assurance of AVs. We have developed an ontology for intersection situations, and used it to generate a situation hyperspace i.e., the space of all possible situations arising from that ontology. For the evaluation of our SitCov AV-testing framework, we have seeded multiple faults in our ego AV, and compared situation coverage based and random situation generation. We have found that both generation methodologies trigger around the same number of seeded faults, but the situation coverage-based generation tells us a lot more about the weaknesses of the autonomous driving algorithm of our ego AV, especially in edge-cases. Our code is publicly available online, anyone can use our SitCov AV-testing framework and use it or build further on top of it. This paper aims to contribute to the domain of V&V and development of AVs, not only from a theoretical point of view, but also from the viewpoint of an open-source software contribution and releasing a flexible/effective tool for V&V and development of AVs.
翻译:自动车辆(AV),即自驾驶汽车,在安全的关键领域运作,因为自主驾驶软件的错误会导致巨大的损失。从统计上看,作为AV操作设计域一部分的公路交叉路口具有一些最高的事故率。因此,对道路交叉路口的限制进行AV测试,并确保其在道路交叉路口的安全,因此是本文的重点。我们为基于情况的VV(SitCov)AV测试框架,用于自动驾驶软件的核实和验证(V&V)以及AV的安全保障,这是在公开源码AV模拟软件的模拟器中开发的。SitCAV模拟器的开发过程。SitCAV测试框架侧重于不同环境和交叉配置情况下的车辆对车辆之间的交互作用,使用自动测试套件的自动交叉路口标准来保证AVs的安全性。我们开发了一种基于我们交错点的Outical VV工具, 并且使用了一种基于AV软件的动态自动测试框架。我们从机检的在线空间,但所有可能的动态空间也用于对ALA的图像的覆盖和生成情况进行比较。