• DocumentCode
    293558
  • Title

    Fuzzy neural traffic control and forecasting

  • Author

    Hellendoorn, Hans ; Baudrexl, Richard

  • Author_Institution
    Corp. Res. & Dev., Siemens AG, Munich, Germany
  • Volume
    4
  • fYear
    1995
  • fDate
    20-24 Mar 1995
  • Firstpage
    2187
  • Abstract
    Fuzzy systems can be used to represent human knowledge. Traffic technology is a science where this property of fuzzy logic can be very well adapted because it is hard to make mathematical models due to human influences and complex connections between input parameters. One example of the use of fuzzy logic in traffic control is in highway speed control systems. The goal is to optimally use the highway. We first describe a fuzzy system for traffic flow control and incident recognition that has been in use for some time. Another example that we describe is fuzzy logic in forecasting whether a particular parking garage is full or not. We describe the input parameters and the structure of the fuzzy system. Furthermore, we show how neural networks can be used to improve the performance of the system
  • Keywords
    fuzzy control; fuzzy logic; fuzzy systems; neural nets; road traffic; traffic control; fuzzy logic; fuzzy neural traffic control; fuzzy system; highway speed control systems; incident recognition; neural networks; traffic condition forecasting; Communication system traffic control; Control systems; Fuzzy control; Fuzzy logic; Fuzzy systems; Humans; Mathematical model; Road transportation; Traffic control; Velocity control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 1995. International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium., Proceedings of 1995 IEEE Int
  • Conference_Location
    Yokohama
  • Print_ISBN
    0-7803-2461-7
  • Type

    conf

  • DOI
    10.1109/FUZZY.1995.409983
  • Filename
    409983