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Research on Real-time Detection of Traffic Information and Bus Arrival Time Prediction Based on Prob

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Tutor: LiPing
School: Zhejiang University
Course: Control Theory and Engineering
Keywords: Floating Car,Bus,Real-time detection,Sample processing,Arrival time prediction
CLC: U495
Type: Master's thesis
Year:  2007
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Intelligent Transportation Systems (ITS) is the transportation industry trends, and real-time traffic information detection is one of the key component. Traditional detection methods in the detection accuracy and real shortcomings, the latest development of the floating car technology has become an important breakthrough point, more and more attention. Floating vehicle technology research around the taxi carrier to start for the deficiencies in the model and sampling theory, this paper presents a the floating bus sample processing method. The method uses the sample data rate of formation of the calibration cycle distribution, re-use the update cycle sample distribution of data validation, verification, to take a different approach. Simulation results show that the method has achieved good results. Secondly, the factors that affect the detection accuracy of the floating bus discussion and simulation confirmed the link length, link flow and the number of samples floating car detection accuracy. Again, to determine the basis of the actual number of samples and the theoretical number of samples in the floating car, defines public transport hot and cold region, improved method of detection accuracy. Floating car sample processing methods, this paper expand catholic delivery of the vehicle arrival time prediction. Simulation results show sections and path-based approach works better contrast arrival time prediction method based on points, roads and paths. Meanwhile, in order to further meet the travel needs of passengers, this paper the advantages based on roads and paths, put forward a comprehensive time prediction methods. Floating car design and completion of the Urban Mixed Traffic Flow Simulation analysis system (SASUMT) floating bus software modules, to provide the conditions for the simulation. The sections of this article is organized as follows: The first chapter introduces the traditional lack of detection technology, the introduction of the research status of the floating car technology, the the floating taxis and floating bus on the model, the sampling and data processing different. At the same time bus arrival time prediction research status quo. The second chapter introduces the the floating bus sample processing method and simulation, discussion and simulation of the impact of factors related to the detection accuracy of the floating bus. Turn to the actual number of samples to make a floating bus, the theoretical minimum number of samples to determine the basis and concepts such as public transport hot and cold regions, to further improve the processing of the sample data. Chapter III on the basis of the detection of the floating bus, forecasting methods based on points, roads and paths bus arrival time, and simulation comparison. At the same time, take into account the needs of passengers comprehensive prediction method. The fourth chapter describes the implementation of the simulation software, object modeling, the main function, interface and program flow are introduced. Chapter V concludes the paper, and future work.
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