Today, traffic congestions at streets became a serious problem specifically in the area with the high population density. In this paper a novel intelligent controller system was proposed and designed to reduce the congestions on the streets. The system consists of two intelligent controllers that are designed to be similar to the human brain in solving problems and finding the best solutions; two main methods are used in the training of the controllers: the first one is the super vised feed-forward neural networks and the second one is the Particle Swarm Optimization (PSO).The results of the two methods are compared with each other and the best one was chosen for the designing. The first intelligent controller was used to check all the streets according to its traffic while the second one is used to determine the necessary time for each street based on the results which are obtained previously from the first controller in order to control the traffic light that allows the vehicles on each street to be moving or waiting its turn.
Volume 11 | 04-Special Issue
Pages: 1528-1539