Decision Making for Autonomous Vehicles at Unsignalized Intersection in Presence of Malicious Vehicles
For developers of autonomous driving systems, this work tackles a safety-critical problem of handling rule-breaking vehicles in intersection coordination, though the approach is incremental as it extends game-theoretic methods to a specific adversarial setting.
This paper addresses decision-making for autonomous vehicles at unsignalized intersections when some vehicles act maliciously by ignoring right-of-way rules. It models the interaction as a game where each vehicle computes a Nash equilibrium based on its own priority belief, and demonstrates the approach through numerical simulations across various scenarios.
In this paper, we investigate the decision making of autonomous vehicles in an unsignalized intersection in presence of malicious vehicles, which are vehicles that do not respect the law by not using the proper rules of the right of way. Each vehicle computes its control input as a Nash equilibrium of a game determined by the priority order based on its own belief: each of non-malicious vehicle bases its order on the law, while a malicious one considers itself as having priority. To illustrate our method, we provide numerical simulations, with different scenarios given by different cases of malicious vehicles.