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Research on Forecasting Vehicle’s Velocity Based on Data from GPS Floating Cars

Author: GongShan
Tutor: YinXiangYong
School: Beijing Jiaotong University
Course: Intelligent Transportation Engineering
Keywords: Floating Car Traffic speed Forecast K-neighbor Markov
CLC: U495
Type: Master's thesis
Year: 2009
Downloads: 430
Quote: 7
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Abstract


Traffic speed is an important indicator of the need to predict one of the important parameters of the traffic state , is also intelligent transportation system . Road traffic flow , density , and other information can be obtained by the speed and provide the basis to predict the road traffic situation in the next period of time ; while analysis of the running state of the traffic flow on the road to control traffic flow feedback data as a synergistic intersection signal control basis , in order to ease the passing vehicles , shortening the travel time , reduce losses , and to ensure safe and smooth traffic . Conventional short-term prediction based on the collected data of the fixed equipment of the coil, etc. , just sections of a cross-section , the distribution is not enough; floating cars are relatively evenly distributed on the road section , through the the GPS vehicle apparatus and a wireless communication device , the vehicle information (such as time , transmitted in real time to the information center of the floating car speed , latitude and longitude coordinates , direction , and other parameters) . Thus , the floating car GPS data collected on the fixed equipment information is a good complement to provide a good foundation for traffic speed prediction . Summary floating cars at home and abroad as well as road travel time , traffic speed , the paper predicted on the basis of the research sections based on the floating car data traffic speed short-term forecasting model study . Based on the floating car data , combined with a history of run of the road network and real-time traffic data , respectively, to establish the K- nearest neighbor prediction model , Grey Markov forecasting model and weighted Markov prediction model . K- neighbor prediction model based on cluster analysis and Pareto efficient solution to the nearest neighbor method for determining ; gray GM (1,1) gray prediction model and Markov theory together ; in the weighted Markov prediction model , traffic information will be state of division , and import model predictive analysis . Papers Hangzhou floating car data , the paper established model sections of traffic speed forecast sample analysis to verify the validity of the model .

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CLC: > Transportation > Road transport > Technical management of traffic engineering and road transport > Computer applications in road transport and highway projects
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