The Study Of Regional Transportation Timing Optimization Base On Improved Particle Swarm Algorithm

With the rapid development of economy and technology, the car has become a routine means of transport, which results in the serious traffic problems. It is the aim that the modern traffic control timing plan to make full use of existing network resources and improve the efficiency of traffic. Hence, in this thesis, we set up the traffic model based on the region, in which, the region in city is as optimization object. Its performance is presented by average minimum travel time of vehicles and its average delay model for single intersection is established by the revised HCM2000.Recently, with the development of artificial intelligence technology, the application of intelligent information processing in real life has become a hot topic. In this thesis, an improved particle swarm optimization(PSO) algorithm is proposed. Then, the algorithm presented in this thesis is used to solve the regional model that the average travel time of area vehicle is the shortest. Finally, the improved particle swarm optimization(PSO) algorithm is used to optimize traffic timing model in three states, that is, the unsaturation state, the saturation state and the mixed state in the large difference of traffic. The experimental results show that the strategy proposed in this thesis can balance the local optimal solution and the global optimal solution, optimize traffic timing parameters, effectively reduce delay, shorten the average vehicle delay, thus shortening regional vehicle average travel time. So the model and algorithm proposed in this thesis not only is reasonable and effective, and has greatly improved the accuracy of the algorithm. Details are as follows:1. An improved particle swarm optimization algorithm is proposed. The algorithm by combined inertia weights with nonlinear strategy.2. In this thesis, the region as a whole optimization goal, the region with the shortest average vehicle traffic as a measure of performance, established a regional average vehicle traveling the shortest mathematical model according to HCM2000 model.3. Using the improved particle swarm algorithm to solve the above model and get the phase timing plan of area in each intersection, which can ease the traffic pressure.