Algorithm development of an intelligent traffic light control system.

Abstract

This study presents an implementation of an intelligent traffic light control system for a crossroads based on combination of image processing and fuzzy controller. After certain seconds of red light, traffic densities are estimated from captured images. Based on this estimated result, a fuzzy controller determines the length of the next green light period in order to generate longer period for higher density road, vice versa. A software was developed to evaluate the suggestion algorithm, and to compare it with traditional timer-based traffic light system. Simulation results indicate that the road with higher traffic flow has a longer green light period, and vice versa. When the traffic’s densities of 2 roads are 5 times different, the vehicle red-light waiting times of the suggested system are reduced from 15 to 20 times better than the traditional system.