Research On Optimization Model And Method Of Intelligent Control For Single Signalized Intersection

With the advance of the city and the number of vehicles increasing,the urban road traffic is facing great pressure,and the delay occurred mainly at the intersection,therefore,intersection signal control plays an important role in the healthy operation of road traffic.Because the traffic system is very complex,the traditional pretimed signal timing method can not adapt to the random traffic flow,The intelligent control method which can adjust the timing scheme in time according to the change of traffic flow becomes an effective solution to improve the efficiency of intersection.Firstly,based on the traditional signal timing,the optimal model of timing control is proposed.In this paper,a multi-objective optimization model based on particle swarm optimization is proposed by considering three indexes of delay,parking rate and capacity.To reduce the delay and the parking rate while increasing the capacity of the intersection,and through the actual case analysis to verify the validity of the model.Secondly,the intelligent control method based on fuzzy control is studied in this paper.The fuzzy control method includes green time delay module and phase sequence optimization module The green time delay module regulates the green time length according to the queue length of the vehicle,The phase sequence optimization module adjusts the phase sequence according to the demand degree of the different phases.The fuzzy control scheme can adjust the timing scheme according to the changing traffic flow and reduce the average vehicle delay.Thirdly,based on the fuzzy control,the neural network is used to establish the fuzzy neural network signal control method in this paper.This method can give full play to the advantages of neural network.A lot of practical data are used to train the fuzzy neural network in order to obtain the intelligent control scheme which can be adapted to different traffic flow.This method can effectively improve the operation efficiency of intersection.Finally,the simulation model of traffic signal control is established based on the actual intersection,and the three control methods are analyzed.Delay comparison shows that the control effect of fuzzy neural network control is the best,the delay is lower than the timing control 20%-30%,the fuzzy control is second,and the delay is lower than the timing control 10%-15%.In this paper,the changing rules of the vehicle queue length and the timing scheme are analyzed in detail,and discusses the relationship between queue length and timing results,verified the correctness of the control method.