OPTIMIZATION OF TRAFFIC LIGHT CONTROL SYSTEM OF AN INTERSECTION USING FUZZY INFERENCE SYSTEM
This paper considers an automated static road traffic control system of an intersection for the purpose of minimizing the effects of traffic jam and hence its attendant consequences such as prolonged waiting time, emission of toxic hydrocarbons from automobiles, etc. Using real-time road traffic data, a dynamic round-robin allocation of right-of-way to road users based on fuzzy inference system (FIS) was implemented as a decision support tool. The static phase scheduling algorithm for traffic light systems was used as a benchmark to measure the performance of our technique which is based on dynamic phase scheduling algorithm. The performance comparison records a significant improvement of about 65.35% in average waiting time. This clearly demonstrates the efficacy and potential of our solution strategy to address the traffic scheduling problem.