• DocumentCode
    2721359
  • Title

    A fuzzy diagnosis process for the detection of evolution of a car driver´s behavior

  • Author

    Peltier, Marie-Agnès ; Lajon, Marc

  • Author_Institution
    ECP/EPAP, Chatenay Malabry, France
  • fYear
    1994
  • fDate
    24-26 Oct. 1994
  • Firstpage
    19
  • Lastpage
    24
  • Abstract
    This paper describes a monitoring and diagnosis process for the detection of evolution of a car driver´s behavior. This is an adaptive fuzzy pattern recognition algorithm that achieves progressive and online learning of the driver´s characteristics. A neural net based architecture associated with a real-time algorithm for the detection of abrupt changes provides a diagnosis of evolution that may also be predictive. Promising results on real data are reported.
  • Keywords
    behavioural sciences computing; computerised monitoring; fuzzy set theory; learning (artificial intelligence); neural nets; pattern recognition; traffic engineering computing; adaptive fuzzy pattern recognition algorithm; car driver´s behavior evolution detection; fuzzy diagnosis; neural net; online learning; progressive learning; Biomedical monitoring; Electroencephalography; Electrooculography; Fatigue; Neural networks; Pattern recognition; Rain; Road accidents; Vehicle driving; Wheels;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Vehicles '94 Symposium, Proceedings of the
  • Print_ISBN
    0-7803-2135-9
  • Type

    conf

  • DOI
    10.1109/IVS.1994.639463
  • Filename
    639463