Research And Implementation Of Urban Regional Traffic Signal Control Technologies

With the rapid development of our country's economy and social progress,as well as the outstanding results achieved by the new urbanization construction,people's living standards continue to improve.The contradiction between the increasing demand for urban transportation and limited urban road transportation resources has become increasingly prominent,causing a series of urgent problems need to be solved,such as traffic congestion,frequent traffic accidents,and pollution emissions.Scholars at home and abroad generally believe that optimizing the traffic signal control strategy of urban city is one of the important means to relieve urban congestion,reduce traffic accidents,and promote energy conservation and emission reduction.Based on the above background,this thesis takes the optimization of regional traffic signal control of urban city as the core,deeply studies the short-term prediction method of urban traffic flow,proposes a distributed regional traffic signal control method,and designs and implements a virtual simulation experimental system that supports distributed regional traffic signal control based on the existing microscopic traffic simulation engine.It has very practical significance and application prospects for alleviating traffic congestion and the series of problems it brings.The main research contents of this thesis are as follows:(1)Improved fuzzy time series short-term traffic flow prediction model based on fuzzy c-means algorithm.This model aims at the shortcomings of domain division and historical data fuzzification in the fuzzy time series short-term traffic flow prediction model based on fuzzy c-means algorithm.It uses the K-nearest neighbor algorithm to optimize the initial clustering center of the fuzzy c-means algorithm,optimizes the number of clusters and considers the discrete degree of the sample set when fuzz historical data.The proposed algorithm improves the prediction accuracy and greatly reduces the number of model iterations.(2)A distributed regional traffic signal coordinated control algorithm is proposed.This algorithm aimes at the shortcomings of the backpressure-based traffic signal control algorithm with fixed phase duration and without considering the effect of intersections on its adjacent intersections.Based on the prediction results of the fuzzy time series shortterm traffic flow prediction model based on K-FCM(K-Nearest Neighbor fuzzy c-means,K-FCM)improved in this thesis,the phase configuration of the back pressure algorithm is improved,and a distributed regional traffic signal coordinated control model is established based on the adjacency relationship of intersections in the road network with considering the queuing effect of intersections on its adjacent intersections.The proposed algorithm reduces the average waiting time and travel time of vehicles in the urban road network.(3)A virtual simulation experimental system supporting distributed regional traffic signal coordinated control is designed and implemented.Based on the existing microscopic traffic simulation engine,the overall architecture and main functional modules of the virtual simulation experimental system supporting distributed regional traffic signal coordinated control are designed,and the main functional modules involved in my development work are implemented.