Optimal control for region of the city traffic signal base on Selective particle swarm optimization algorithm

Through the analysis for the current urban road network and the urban traffic control schemes, establish the model of the average of vehicle up-time in road network. Then, by use for reference thinking of natural selection of genetic algorithm improved the minimum value problem of particle swarm optimization algorithm. Hereafter, the model was optimized by the improved particle swarm optimization, and the solving result when the model is the minimum value is the optimal timing scheme of each intersection within the region. Finally, collecting traffic information through the regional road network consisting of four-way intersection near the school, and this data as the basis to build a four-way intersection area network in VISSIM5.20 software, and making simulation experiment of the comparison of the optimization model and traditional timing scheme by MATLAB software. The results of the analysis according to the simulation experimental shows that the average running time of all vehicle of region increase about 24.1 percent, and the average delay time of all Intersection reduce about 27.4 percent. In a certain extent, Improve the efficiency of regional transit traffic and ease urban traffic pressure, and has some applicability.