Refining Abstract Specifications into Dangerous Traffic Scenarios

Safety assurance of autonomous vehicles (AVs) is particularly challenging when considering the infinite number of scenarios an AV may encounter. As such, existing scenario generation approaches optimize search to derive dangerous refinements of a (same) abstract scenario given as input. In this paper, we propose a scenario generation approach that derives dangerous (collision-inducing) concrete scenarios from arbitrary abstract scenarios (under reasonable assumptions). As added novelty, our approach allows to compare the level of danger offered by different abstract scenarios. We evaluate the collision avoidance capacity of the Transfuser AV controller by generating, then simulating, collision-inducing 2-actor scenarios at a road junction. Results show that distinctions at higher abstraction levels yield measurable differences in simulation.