Study On The Methods Of Traffic State Identification For Urban Road Based On Date Fusion

At present,with traffic congestion emerging frequently which become the difficult challenge all over the world,several problems have been brought about,such as traffic delay increasing,traffic safety decreasing and cost wasting hugely,which have been disturbing the living of people more and more. To alleviate the negative effect of congestion,it is very necessary to provide the traffic managers and the travelers with the information on the traffic state newly and reliably. If the traffic congestion could be identified accurately,the traffic managers could adopt the effective traffic management measures to reduce the severity extent of the traffic congestion.The thesis stems from the National High-tech Research and Development Program (863) project"The key technology research and development of new generation of intelligent traffic control system"(2006AA11Z228)sub items"collection technology of traffic control related condition". On account of the problems at present,such as the complex urban road type,kinds of detectors and no uniform measurement standard of traffic state,the thesis introduces the advanced information processing technologies including Fuzzy and Statistical analysis from the perspective of theory and practice,in order to study ACI methods on fixed detector data and mobile detector data in urban road. Aiming at the inconsistent traffic state in different ACI algorithm , the thesis also puts forward the decision-making integration of ACI algorithm.The thesis comprises of 7chapters and their contents are as follows:Chapter One: Introduction. First,introduce the subject sources and propose the study content. Then,present the history and status. At last,make certain the main content of the thesis is given.Chapter Two: Research foundation. Firstly,introduce the type of urban road and characteristic of traffic flow. Then,summarize usual traffic information collection methods in current city road. Next,the thesis determines the time interval of the traffic conditions identification according to the needs of traffic users and the performance of traffic parameters. Finally,present the index and method evaluating the performance of traffic identification algorithms.Chapter three: Research of traffic state measurement standard in urban road. Firstly,define traffic state in urban road and make sure that the thesis classes the traffic state into smooth,general congestion,severe congestion. Each traffic state should have the corresponding measurement standard. Therefore this chapter focuses on the measurement standard of the traffic state and the corresponding measurement method.Chapter four: The study of automatic traffic state identification algorithm using mobile detector data for urban road. After reviewing the general identification algorithms,the detailed design process of algorithm based on the travel speed of link is available,because the class of traffic state is different in conventional algorithms and new algorithm. Then,analyses the relationship between samples of the car and the reliability of the traffic state and make sure the function relation between reliability and samples of the car. Lastly,simulation data are used to calibrate and test the innovative algorithm.Chapter five: the design of automatic traffic state identification algorithms using fixed detector data for urban road. First,introduce the Fuzzy theory. On this basis,the ACI algorithms using fixed detector data are proposed,and their detailed design process is presented. Then analyze the traffic data from the detector which is emplaced in the different location of urban road,and make sure the input parameters of ACI Algorithm in corresponding position. After that,the thesis calibrates and tests the new designed algorithms using simulation data.Chapter Six: the study of decision-making integration of ACI algorithm for urban road. Firstly introduce the general decision-making integration algorithm at present. Then based on the characteristics of data integration and fuzzy comprehensive evaluation method,the thesis determines the decision-making integration algorithm and the basic application framework Chapter Seven: Conclusions and the future work. The main contents of the thesis are reviewed,and then the innovation and the existing problems are pointed out. Finally,the problems that need to further study in the future are proposed.