An Intersection Game Theory Based Traffic Control Algorithm in a Connected Vehicle Environment
Urban traffic congestion is a growing problem that we experience every day. Intersections are one of the major bottlenecks that contribute to urban traffic congestion. Traditional traffic control methods, such as traffic signal and stop sign control are not optimal for all demand levels as demonstrated in the literature. Recently, numerous research efforts proposed Intelligent Transportation System (ITS) applications to enhance intersection capacity and hence reduce congestion. In this paper we propose a game theory based algorithm for controlling autonomous vehicle movements equipped with Cooperative Adaptive Cruise Control (CACC) systems at uncontrolled intersections. The goal of this research effort is to develop an algorithm capable of using the future autonomous/automated vehicle capabilities to replace the usual state of the practice control systems at intersections (e.g. stop signs, traffic signals, etc. The proposed algorithm is chicken game inspired and is efficient for application in real time. It assumes vehicles can communicate with a central agent at the intersection to provide their instantaneous speeds and locations. The proposed algorithm assumes that vehicles obey the Nash equilibrium solution of the game. The simulation results demonstrated reductions in vehicle travel time and delay relative to an all way stop sign control in the range of 49 and 89 percent on average respectively.
2015 IEEE 18th International Conference on Intelligent Transportation Systems