Optimization of Traffic Flow within an Urban Traffic Light Intersection with Genetic Algorithm

• Published in: 2010 Second International Conference on Computational Intelligence, Modelling and Simulation pp. 172 - 177
• Main Authors: Teo, K T K, Kow, W Y, Chin, Y K
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.09.2010
• Subjects: Biological cells; Delay effects; Genetic Algorithm; Optimization; Roads; Simulation; TJunction; Traffic control; Traffic Control System; Traffic Flows; Vehicles
• ISBN: 1424486521; 9781424486526
• ISSN: 2166-8523
• DOI: 10.1109/CIMSiM.2010.95

Traffic flow control optimization in the traffic light systems is studied for improvement in this paper. Traffic light systems are built to control the traffic flows at the intersections to ensure the fluency of traffic flow within the traffic network. The increasing traffic flows that cannot be supported by the current traffic light systems cause lengthen of queue length at the intersection. The effect of queue length, green time, cycle time and amber time in the traffic system is observed and studied through simulations. Longer green time will pass through more vehicles, but it will increase the cycle time at the same time which causes more vehicles to accumulate at the intersection during the waiting time. Genetic algorithm is introduced in this paper for the optimization of the traffic flow control as its ability to find the optimized solution in its self tuning process. Genetic algorithm taking current queue length as its input then it will output the optimized green time for the intersection. The result of Genetic algorithm is further improved with the introduced of the incoming traffic flow during red time of each phase.