Traffic lights optimization with distributed ant colony optimization based on multi-agent system

Abstract

Traffic congestion in road networks increase the rate of vehicles at each road and decrease the average of circulation in intersections, this problem can be controlled and managed with some strategies and measures that reduce the number of demand on the road network. Today Traffic signal timing control is a useful technique to control traffic movement to avoid and reduce traffic jam. In industrial cities, the increase of population led to the problem of traffic congestion, where this kind of problem needs intelligence systems to control traffic flow based on artificial intelligence. In this paper, we try to implement a distributed ACO algorithm for optimizing traffic signal timing based on the main objective of self-organization, collective of the ACO algorithm to simulate the traffic road network. The proposed method aim to manage intersections in real time using a decentralized algorithm of ant colony optimization to decrease the traffic flow based on the signal timing and a set of inputs data from the runtime environment.