Cooperative game-theoretic approach to traffic flow optimization for multiple intersections

Abstract

In this study, we focus on optimizing traffic flow at multiple intersections. Particularly, with the development of Internet of Things, intersection controllers are regarded as smart agents which can communicate and coordinate with each other. In this regard, a cooperative game theoretic approach among agents is proposed to improve traffic flow with large network. Thereby, a distributed merge and split algorithm for coalition formation is presented. This algorithm is applied to find out how to incorporate with the cooperation among agents for dynamically controlling traffic light at intersections. Furthermore, we construct a traffic simulation framework to evaluate our approach. With various parameters for traffic density, our proposed system can effectively improve traffic flow in both uniform and non-uniform. In particular, by coordinating among controllers, the waiting time of vehicles at intersections can be reduced from 15% to 25% comparing with previous methods (e.g., Green Wave Coordination).