Real-Time Freeway Traffic State Estimation Based on Extended Kalman Filter: A Case Study

The authors present a real-time traffic state estimation case study. The authors outline extended Kalman filtering and stochastic macroscopic traffic flow modeling, which form the basis for the adopted general approach to freeway stretch universal traffic state estimators design. Using a 4.1 km Munich, Germany-area freeway stretch, eight hour traffic measurement data was collected for the investigations reported on by the authors. Some of the key issues investigated include biased flow measurement handling capability of the estimator, standard deviation values related noise sensitivity by the estimator, estimated model parameter initial values sensitivity by the estimator, online model parameter estimation significance, and designed traffic state estimator tracking capability. The authors found achieved results quite satisfactory.

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  • Authors:
    • Wang, Yibing
    • Papageorgiou, Markos
    • Messmer, Albert
  • Publication Date: 2007-5


  • English

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  • Accession Number: 01050200
  • Record Type: Publication
  • Files: TRIS
  • Created Date: May 24 2007 3:54PM