Traffic Condition Recognition of Probability Neural Network Based on Floating Car Data

  • Authors:

  • Gengqi Guo;Chengtao Cao;Jiuzhong Li;Shuo Shi

  • Affiliations:

  • South China University of Technology, Guangzhou, China 510640 and Guangdong Communication Polytechnic, Guangzhou, China 510650;South China University of Technology, Guangzhou, China 510640 and Guangdong Communication Polytechnic, Guangzhou, China 510650;Guangdong Industry Technical College, Guangzhou, China 510300;Guangdong Industry Technical College, Guangzhou, China 510300

  • Venue:
  • ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III
  • Year:
  • 2009

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Abstract

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.