Title: Design of traffic signal automatic control system based on deep reinforcement learning

Authors: Haoyu Wang

Addresses: Information Engineering Department, Southwest Jiaotong University Hope College, Chengdu, Sichuan, China

Abstract: Aiming at the problem of aggravation of traffic congestion caused by unstable signal control of traffic signal control system, the Multi-Agent Deep Deterministic Policy Gradient-based Traffic Cyclic Signal (MADDPG-TCS) control algorithm is used to control the time and data dimensions of the signal control scheme. The results show that the maximum vehicle delay time and vehicle queue length of the proposed algorithm are 11.33 s and 27.18 m, which are lower than those of the traditional control methods. Therefore, this method can effectively reduce the delay of traffic signal control and improve the stability of signal control.

Keywords: traffic signal; automatic control; deep reinforcement learning; MADDPG-TCS; multi-agent.

DOI: 10.1504/IJWMC.2024.142071

International Journal of Wireless and Mobile Computing, 2024 Vol.27 No.4, pp.381 - 392

Received: 11 Oct 2023
Accepted: 01 Mar 2024
Published online: 07 Oct 2024 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article