Run-Time Risk Mitigation in Automated Vehicles: A Model for Studying Preparatory Steps
This work addresses safety assurance for autonomous driving systems, but it appears incremental as it builds on existing modeling approaches without introducing a fundamentally new paradigm.
The paper tackles the challenge of ensuring safety in automated vehicles by proposing a model for analyzing hazards and designing mitigation strategies, demonstrating its applicability through an example and enabling formal verification of safety properties.
We assume that autonomous or highly automated driving (AD) will be accompanied by tough assurance obligations exceeding the requirements of even recent revisions of ISO 26262 or SOTIF. Hence, automotive control and safety engineers have to (i) comprehensively analyze the driving process and its control loop, (ii) identify relevant hazards stemming from this loop, (iii) establish feasible automated measures for the effective mitigation of these hazards or the alleviation of their consequences. By studying an example, this article investigates some achievements in the modeling for the steps (i), (ii), and (iii), amenable to formal verification of desired properties derived from potential assurance obligations such as the global existence of an effective mitigation strategy. In addition, the proposed approach is meant for step-wise refinement towards the automated synthesis of AD safety controllers implementing such properties.