Adaptive Traffic Light Control with Statistical Multiplexing Technique and Particle Swarm Optimization in Smart Cities

Vehicular traffic in Urban areas of the globe is continuously increasing and the resulting congestion has become a major concern for transportation management. The traffic signal controls are the major way to manage vehicular flow at the intersections in these urban areas. However, traditional systems fail to adjust the timing pattern based on traffic which demands for need of developing adaptive systems. The focus is this study is to develop an intelligent system that is adaptive to the traffic flow at an intersection point of the real scenarios. A hybrid system comprising of Statistical Multiplexing and Particle Swarm Optimization(PSO) has been developed to control the flow of traffic. The performance of the developed algorithm was tested with both simulated and real traffic count of some major traffic congestion intersection of Kathmandu valley. It was observed that the average waiting time of vehicles on a junction has been reduced.