Least Restrictive Supervisors for Intersection Collision Avoidance: A Scheduling Approach

We consider a cooperative conflict resolution problem that finds application, for example, in vehicle intersection crossing. We seek to determine minimally restrictive supervisors, which allow agents to choose all possible control actions that keep the system safe, that is, conflict free. This is achieved by determining the maximal controlled invariant set, and then by determining control actions that keep the system state inside this set. By exploiting the natural monotonicity of the agents dynamics along their paths, we translate this problem into an equivalent scheduling problem. This allows us to leverage existing results in the scheduling literature to obtain both exact and approximate solutions. The approximate algorithms have polynomial complexity and can handle large problems with guaranteed approximation bounds. We illustrate the application of the proposed algorithms through simulations in which vehicles crossing an intersection are overridden by the supervisor only when necessary to maintain safety.National Science Foundation (U.S.) (Award CNS 0930081