Controlling a network of signalized intersections from temporal logical specifications

We propose a framework for generating a control policy for a traffic network of signalized intersections to accomplish control objectives expressed in linear temporal logic. Traffic management indeed calls for a rich class of objectives and offers a novel domain for these formal methods tools. We show that traffic networks possess structural properties that allow significant reduction in the time required to compute a finite state abstraction. We further extend our approach to a probabilistic framework by modeling the traffic dynamics as a Markov Decision Process.