2023/05/15 by Megan Strauss, Strauss, Megan, Stefan Mitsch +1
Computer Science · Engineering · #Autonomous Vehicle Technology and Safety #FOS: Computer and information sciences #FOS: Electrical engineering #Formal Methods in Verification #Logic in Computer Science (cs.LO) #Safety Systems Engineering in Autonomy #Software Engineering (cs.SE) #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2305.08812
openalex publication_date 2023/05/15 · openalex created_date 2023/05/17 · openalex updated_date 2026/07/28
Technology advances give us the hope of driving without human error, reducing vehicle emissions and simplifying an everyday task with the future of self-driving cars. Making sure these vehicles are safe is very important to the continuation of this field. In this paper, we formalize the Responsibility-Sensitive Safety model (RSS) for self-driving cars and prove the safety and optimality of this model in the longitudinal direction. We utilize the hybrid systems theorem prover KeYmaera X to formalize RSS as a hybrid system with its nondeterministic control choices and continuous motion model, and prove absence of collisions. We then illustrate the practicality of RSS through refinement proofs that turn the verified nondeterministic control envelopes into deterministic ones and further verified compilation to Python. The refinement and compilation are safety-preserving; as a result, safety proofs of the formal model transfer to the compiled code, while counterexamples discovered in testing the code of an unverified model transfer back. The resulting Python code allows to test the behavior of cars following the motion model of RSS in simulation, to measure agreement between the model and simulation with monitors that are derived from the formal model, and to report counterexamples from simulation back to the formal model.