AN APPROACH OF INTERSECTION TRAFFIC SIGNAL CONTROL

This paper discusses a method of intersection traffic signal control with online self-learning ability. The control system is composed of intersection, two neural networks and a performance-evaluation unit. Two neural networks are always alternatively in the state of learning or working during the process of self-learning according to the decision of the performance evaluation unit on the traffic conditions of intersection. Simulation results reveal that the proposed approach can better fit the actual traffic conditions than old ones, and thus it has reached at the goals of making good use of intersections.