Abstract:
Installation of traffic signals is an essential prerequisite for effective functioning and to control traffic congestion in urban areas. Intelligent traffic signal control system is considered more effective to manage large queues of vehicles at junctions. In this research, an intelligent traffic signal system is simulated by an integrated Geographical Information System (GIS), traffic simulation and optimization framework, which is aimed to maximize the numbers of vehicles passing through a traffic junction in minimum amount of time through traffic signals cycle optimization. GIS is incorporated to process the data, provide user interface and for the visualization of results. For optimizing traffic signals, Particle Swarm Optimization (PSO) is performed which consider fitness evaluation and velocity value of associated particles to get successful optimization. Fitness measure is a function that measures the closeness of the obtained solution to the given objective. Optimization of traffic signals at mentioned study areas is evaluated in a simulation model, namely, Simulation of Urban MObility (SUMO). The results obtained from baseline and PSO algorithm applied methods are compared with default trip generated in simulation model. Mean travel time for both SUMO-TLS as well as PSO-TLS were collected, simulated, analyzed and compared. Optimized system shows 12% decrease in mean travel time. Mean waiting time of each vehicles moving in traffic light system generated by PSO algorithm is 10% less than SUMO-TLS. PSO traffic light system shows less mean travelling time and mean waiting time as compared to the traffic lights generated in SUMO.
