Based on evolutionary algorithm and cellular automata combined traffic signal control

Dynamic signal control is complex but important to develop a city intelligent transportation system, which is the best measure to solve the urban traffic jam problem all over the world. In this paper, the mathematical model of traffic signal control based on the classic BML models was introduced, then combines evolutionary algorithm with cellular automata simulation to calculate travel time and optimize signal setting plan. Iterative simulation and assignment procedure is built: Road is discredited by cellular automata. Traffic flow dynamics is represented by the combined model; Signal setting is optimized by evolutionary algorithm. The results of the simulation show that it is to be very promising and can meet the needs in the research and design of intelligent traffic system.