Science and Technology Studies Commons^™

An Edge Based Multi-Agent Auto Communication Method For Traffic Light Control, Qiang Wu, Jianqing Wu, Jun Shen, Binbin Yong, Qingguo Zhou

Faculty of Engineering and Information Sciences - Papers: Part B

With smart city infrastructures growing, the Internet of Things (IoT) has been widely used in the intelligent transportation systems (ITS). The traditional adaptive traffic signal control method based on reinforcement learning (RL) has expanded from one intersection to multiple intersections. In this paper, we propose a multi-agent auto communication (MAAC) algorithm, which is an innovative adaptive global traffic light control method based on multi-agent reinforcement learning (MARL) and an auto communication protocol in edge computing architecture. The MAAC algorithm combines multi-agent auto communication protocol with MARL, allowing an agent to communicate the learned strategies with others for achieving global optimization …