吉林大学学报(工学版) ›› 2014, Vol. 44 ›› Issue (3): 648-654.doi: 10.13229/j.cnki.jdxbgxb201403011

• Orignal Article • Previous Articles     Next Articles

Application of fuzzy Kalman filter in travel time estimation in urban expressway

HUANG Yan-guo1,2, XU Lun-hui1, KUANG Xian-yan2   

  1. 1.School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510640, China;
    2.School of Electrical Engineering & Automation, Jiangxi University of Science & Technology, Ganzhou 341000, China
  • Received:2012-11-30 Online:2014-03-01 Published:2014-03-01

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Abstract: First, the new information was defined and its change was online monitored. The mean and variance of new information were input into the fuzzy controller. Then, the fuzzy logic was used to adjust the importance weights of system noise and observation noise. The new method overcomes the shortcomings of traditional filter, which can not real-time track the change of environment. It adapts to the dynamic change of traffic state to realize the optimization estimation. The method was tested on urban expressway in Guangzhou using real-time detection data. The results show that the proposed method has better tracking ability than traditional Kalman filter. There was a slight difference between the prediction result and that of actual observation in free traffic flow state and stable flow, and the relative error was under 10% in congested traffic state.

Key words: engineering of communications and transportation system, urban expressway, travel time prediction, adaptive Kalam filter, fuzzy logic

CLC Number: 

  • U491.14
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