• DocumentCode
    1814413
  • Title

    A new algorithm of incident detection on freeways

  • Author

    Wen, Huimin ; Yang, Zhaosheng ; Jiang, Guiyan ; Shao, Changfeng

  • Author_Institution
    Coll. of Transp., Jilin Univ., China
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    197
  • Lastpage
    202
  • Abstract
    With the high development speed of the Chinese economy, lots of new freeways have been constructed. Hence, incident management becomes an important issue in the freeway traffic management system. Because incident detection is a kind of pattern recognition problem, in this paper we employed the probabilistic neural network (PNN) to solve it. Applying traffic simulation software FRESIM, a wide range of incidents that include different patterns under a variety of flow conditions and traffic periods were generated to train and evaluate the performance and the transferability of the proposed PNN-based algorithm. It was proved that the models of our proposed algorithm built on one segment can be used for other segments, and all three performance measures indicated the potential of practical use of them
  • Keywords
    automated highways; learning (artificial intelligence); neural nets; pattern recognition; road traffic; traffic engineering computing; FRESIM traffic simulation software; flow conditions; freeway incident detection; freeway incident management; freeway traffic management system; neural net training; pattern recognition problem; probabilistic neural network; traffic periods; Disaster management; Educational institutions; Neural networks; Pattern recognition; Road accidents; Road safety; Road transportation; Telecommunication traffic; Traffic control; Vehicle safety;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Vehicle Electronics Conference, 2001. IVEC 2001. Proceedings of the IEEE International
  • Conference_Location
    Tottori
  • Print_ISBN
    0-7803-7229-8
  • Type

    conf

  • DOI
    10.1109/IVEC.2001.961753
  • Filename
    961753