RSS+: Pro-Active Risk Mitigation for AV Safety Layers based on RSS

Abstract

Addressing safety for future autonomous vehicles (AVs) while maintaining a high practicability, i.e. not using excessive safety margins, getting stuck or not able to drive at all, is still an open research question. In this regard, the Responsibility Sensitive Safety (RSS) approach, which is a formal parametric safety model, is a promising concept and is currently gaining lots of attraction. With RSS it is possible to combine safety and practicability, if the model parameters are chosen in a reasonable manner, i.e. good enough to achieve a desirable level of safety, but not covering the physical worst case. However, as we will show in this work, this can lead to a not optimal behavior of the AV in extreme situations, when other traffic participants violate RSS assumptions. To overcome this, we propose an extension to RSS, called RSS +, which can mitigate many of these situations in a pro-active manner, without sacrificing practicability.