Modeling Technology And Optimization Method Of Urban Road Traffic Congestion Situation Assessment

Urban traffic congestion has become a stubborn disease that restricts the sustainable development of cities.On the one hand,the research on urban road traffic congestion in China is not uniform and systematic is lacking;on the other hand,the theory is strong,but the practicability is lacking.Starting from the analysis of the characteristics of urban road traffic congestion in China,it is of great practical significance to develop the evaluation model,prediction model,optimization model and control strategy of urban road traffic congestion.This dissertation mainly carried out the following five aspects of the work,committed to the government departments,travel residents,scientific researchers and so on to evaluate,predict,optimize,control urban road traffic congestion to provide new research ideas and methods:1.The causes of urban traffic congestion are studied and the evaluation index system of urban traffic congestion is established.This dissertation summarized the research findings of congestion research from four perspectives and pointed out the problems.By studying the types of congestion,the mechanism of congestion evolution and the measures of congestion evaluation,combined with the reality of our country,the evaluation index system of urban road traffic congestion is constructed with three levels of macro,medium and micro levels,and the basic functions,quantitative methods and interconnections of all levels of congestion evaluation indexes are determined.2.The comprehensive evaluation method of urban road network traffic congestion is studied,and a comprehensive congestion evaluation method based on fuzzy neural network is proposed.The evaluation method of traffic congestion in urban road network at home and abroad is studied.Through the analysis of the relationship between the influence factors of urban road traffic congestion and the traffic congestion in China in recent years,a comprehensive evaluation method,based on fuzzy neural network,is proposed,based on the fuzzy neural network,based on the evaluation index of the traffic congestion,and a comprehensive evaluation method is proposed to reflect the traffic congestion level of urban road network based on the fuzzy neural network,called TFI.Fuzzy neural network-Evaluation Index(TFI)is used to illustrate the feasibility of the method.3.The prediction model of urban road traffic congestion is studied,and a congestion prediction algorithm based on CS-SVR is proposed.Based on the analysis of single model prediction technology and fusion model prediction technology,a road traffic congestion prediction algorithm based on CS and support vector machine regression(SVR)model is proposed.The common SVM prediction method and the CS-SVR prediction method proposed in this paper are compared and analyzed.It is proved that the precision of this algorithm is higher.In addition,the evaluation method of urban road network traffic congestion situation based on CS-SVR is studied,and the feasibility of the method is verified by an example.4.The optimization models of urban road are studied,and an optimization model of urban road network is proposed.The game relationship between urban road network traffic congestion and traffic congestion is analyzed from three aspects of urban road network performance,environmental impact and investment cost.An optimization model of urban road network traffic congestion based on multi-layer objective optimization is constructed,and the optimal balance relationship between road network traffic efficiency,environmental impact and road network construction cost is sought,which is a city for urban road network.The road network optimization decision direction provides reference.5.The traffic congestion control strategies of urban road are studied.The urban traffic congestion control strategies based on signal control and demand management are summarized,and the definition problem of traffic flow pattern division of signal control intersection is focused on.A new intelligent signal control method based on cluster analysis is proposed.Urban traffic congestion control strategies based on planning management are finally verified by actual cases.