Modeling and Simulation of Adaptive Traffic Control System for Multi-Intersection Management using Cellular Automaton and Queuing System

Abstract

During last years, urban traffic has become one of the most studied research topics. This is mainly due to the enlargement of the cities and the growing number of vehicles traveling in this road network. One of the most sensitive problems is to verify if the intersections are congestion-free. Another related problem is the automatic reconfiguration of the network without building new roads to alleviate congestions. These problems require an accurate model to determine the steady state of the traffic. The present article proposes an adaptive traffic light system based on the BCMP network queuing and cellular automata. The aim of this work is to predict the best red and green time span by combining three important factors: The queue length, the evacuation time and the capacity of the destination roads. This approach can maximize the number of vehicles passing intersection and at the same time can minimize the average waiting time of vehicles as a result reducing the congestion and keep the fluency in intersections. To validate our results, we compared our model with a fixed model to explain the strengths of our proposed algorithm.