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

被引：0

作者：

Wang, Haoyu ^{[1
]}

机构：

[1] Information Engineering Department, Southwest Jiaotong University Hope College, Sichuan, Chengdu

来源：

International Journal of Wireless and Mobile Computing | 2024年 / 27卷 / 04期

关键词：

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

D O I：

10.1504/IJWMC.2024.142071

中图分类号：

学科分类号：

摘要：

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 Gradientbased 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. © 2024 Inderscience Enterprises Ltd.

引用

页码：381 / 392

页数：11

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