Communicate with Traffic Lights and Vehicles Based on Multi-Agent Reinforcement Learning

In this paper, we propose a new traffic control method based on multiagent reinforcement learning and communication flow for autonomous vehicles and traffic lights. With the aim to ease traffic overload flow, traffic lights smartly tune the time of green light according to a crossroad situation. Beyond that, crossroad situation information can be transferred between traffic lights and autonomous vehicles. Due to the communication dispatch algorithm, autonomous vehicles can dynamically design new routes for avoiding traffic jams and traffic lights dynamically adjust to real-time traffic more efficiently. We demonstrate that our method outperforms the traditional traffic control method and provides high practicability in the future for autonomous vehicles.