A Hybrid Fuzzy-Genetic Controller for a multi-agent intersection control system

Abstract

Over the years, traffic congestion has grown into one of today's global problems. Intersections are a major cause of this problem. Thus proper management of the intersections, will reduce congestion consequently. In this study, an intelligent Intersection Control System (ICS) is proposed to control traffic flow in intersections. Treating the problem as a Multi-Agent System (MAS), two types of agents inhibit this environment. The Intersection Manager Agent (IMA) is responsible for vehicles coordination in the intersection. The Driver Agent (DA) is implemented on each vehicle to control it. Through predicting the trajectories of the vehicles, minimizing their travel times is possible while avoiding any predicted collision.