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Based on the analysis of floating car traffic information acquisition and processing system structure and construction frame, combining the Zibo floating car features and road conditions, using historical data provided by Zibo city bus companies, adopting the ArcGIS Engine of ESRI company as a map components, putting forward the nearest point estimate map matching algorithms, combining data fusion technology based on Kalman filter and road running speed calibration algorithm, predicting road traffic running status in certain period and express it in the GIS map, this paper completed the design, the practice has proved the suggested method is feasible. [ABSTRACT FROM AUTHOR]

A traffic condition recognition method based on floating car data was proposed by analyzing Probability Neural Network (PNN) and Global K-means algorithm. The related factors of traffic condition and the collection method of floating car data were presented. A probability neural network classifier was designed using Global K-means algorithm and applied to the recognition of traffic condition with floating car data. The experiment results showed that the method could recognize traffic condition well. The accurate rate is satisfactory. [ABSTRACT FROM AUTHOR]