Online Safety Assessment of Automated Vehicles Using Silent Testing

Abstract

Safety validation is a challenge for releasing automated driving, even though substantial effort has been made in this field. This paper proposes an online safety validation method within the frame of virtual assessment of automation in field operation (VAAFO). The basic idea of VAAFO is that a virtual automated vehicle runs in the background, while the physical vehicle is driven in an automated or manual mode. The virtual automated vehicle receives input from real sensors, but has no access to the actuators. Thus, the risk-free nature of simulation-based testing and the validity of field operational testing are combined. The testing of automated vehicles is accelerated by applying the approach in customer vehicles. In this paper, we elaborate on and implement this approach. Essential parameters are studied and specified, while the necessary coordinate transformation is performed. Triggers are defined and concretized by a newly developed criticality index. Two derived simulated cases and a real-world case are utilized to illustrate the VAAFO approach. The study cases show that the safety of automated vehicles can be assessed online and critical scenarios can be discovered by the defined triggers under the framework of VAAFO. The results demonstrate that the proposed approach is able to safely and efficiently test automated vehicles online under real driving conditions and discover unknown unsafe scenarios.