The application of particle swarm optimization on intelligent transport system

With analyzing current traffic problems, the passage pointed out that it can effectively avoid traffic jam by adjusting the time of traffic lights. It adapted optimization algorithm to prove the result by building up a model to analysis. The algorithm that we chose was particle swarm optimization, for this algorithm can build up a signal manage system model easily with considering less complicated factors, and it led to the result that we can get the data more accurate. We established a model that simulated crossing conditions. In the processing of algorithm, we altered the traffic problem into a mathematics question. The traffic intersection model that we built was mainly based on intelligent transport system, as intelligent signal manage system was the core of intelligent transport system. The result of the algorithm proved that traffic will be smoother if we can adjust the time of traffic light from red to light reasonably and effectively.