Multi-intersections traffic signal intelligent control using collaborative q-learning algorithm

Since congestion of traffic is ubiquitous in the modern city, optimizing the behavior of traffic lights for efficient traffic flow is a critically important goal. However,agents often select only locally optimal actions without coordinating their neighbor intersections. In this paper, an urban road traffic area-wide coordination control algorithm based on collaborative Q-learning is proposed. The agent model of traffic intersections is demonstrated. The algorithm substantially reduces average vehicular delay by using a collaborative Q-learning algorithm and can cooperative control of multiple intersections to achieve a near optimal control policy. The computer simulation results show that the control algorithm can effectively reduce the average delay time and play a very good control effect with multi-intersections, so the coordination method used in this paper is effective.