Fuzzy Controller Design Of Intelligent Traffic System Based On Particle Swarm Optimization Algorithm

Nowadays,with the increasing urbanization in China,the intelligent transportation system has made great progress.The existing intelligent traffic control system is basically aimed at the control of traffic signal lights and traffic diversion,but the intelligent traffic control system considering the improvement of traffic and fuel consumption can also be studied.Therefore,this paper studies the fuzzy controller of intelligent traffic system based on particle swarm optimization algorithm and the optimal velocity trajectory planning.The detection of this paper methods will be elaborated firstly in several common intelligent transportation,and focus on the use of video detection methods.After the relevant parameters are detected,the fuzzy controller at the main intersection is designed and studied.The number of vehicles queuing in the north-south direction and the east-west direction is taken as the input,and the sequence of traffic lights and the green time delay in the corresponding direction are taken as the output.For multiple intersections,a certain speed trajectory planning is carried out at first,which is combined with the coordination fuzzy controller to optimize the entire traffic network.The coordination fuzzy control system still takes the basic situation of vehicles at each intersection as the input and the green light delay correction as the output.In this process,particle swarm optimization algorithm was used to optimize the output correction.Finally,Matlab and Paramics simulation were used to simulate the designed multi-intersection fuzzy control system based on particle swarm optimization.In the simulation system,the combination of particle swarm optimization based fuzzy control system and the optimal velocity trajectory can effectively play the expected role.Compared with the previous simple traffic signal control system,the control effect produced by this design has certain advantages.