• DocumentCode
    2052373
  • Title

    Data mining tools for real-time traffic signal decision support & maintenance

  • Author

    Hauser, Trisha A. ; Scherer, William T.

  • Author_Institution
    Virginia Univ., Charlottesville, VA, USA
  • Volume
    3
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    1471
  • Abstract
    This paper describes research investigating the application of data mining tools to aid in the development of traffic signal timing plans. A case study was conducted to illustrate that the use of hierarchical cluster analysis can be used to automatically identify time-of-day (TOD) intervals,, based on the data, that support the design of a TOD signal control system. The cluster analysis approach is able to utilize a high-resolution system state, definition that takes full advantaged of the extensive set of sensors deployed in a traffic signal system and cluster validation supports the hypotheses presented. The results of this research indicate that advanced data mining techniques hold high potential to provide automated signal control techniques
  • Keywords
    data mining; decision support systems; pattern clustering; road traffic; traffic control; traffic engineering computing; data mining; hierarchical cluster analysis; intelligent transportation systems; time-of-day intervals; traffic signal timing; Automatic control; Automatic generation control; Control systems; Data mining; Intelligent sensors; Intelligent transportation systems; Sensor systems; Signal analysis; Signal processing; Timing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 2001 IEEE International Conference on
  • Conference_Location
    Tucson, AZ
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-7087-2
  • Type

    conf

  • DOI
    10.1109/ICSMC.2001.973490
  • Filename
    973490