A Reinforcement Learning-Based Distributed Control Scheme for Cooperative Intersection Traffic Control

Guzman, Jose A.; Pizarro, German; Nunez, Felipe

A Reinforcement Learning-Based Distributed Control Scheme for Cooperative Intersection Traffic Control

Date

2023

Authors

Guzman, Jose A.

Pizarro, German

Nunez, Felipe

Abstract

Traffic congestion is a major source of discomfort and economic losses in urban environments. Recently, the proliferation of traffic detectors and the advances in algorithms to efficiently process data have enabled taking a data-driven approach to mitigate congestion. In this context, this work proposes a reinforcement learning (RL) based distributed control scheme that exploits cooperation among intersections. Specifically, a RL controller is synthesized, which manipulates traffic signals using information from neighboring intersections in the form of an embedding obtained from a traffic prediction application. Simulation results using SUMO show that the proposed scheme outperforms classical techniques in terms of waiting time and other key performance indices.

Keywords

Predictive models, Detectors, Real-time systems, Data models, Urban areas, Graph neural networks, Decentralized control, Reinforcement learning, cyber-physical systems, intersection control, distributed control