• DocumentCode
    3264744
  • Title

    Severity Analyses of Single-Vehicle Crashes Based on Rough Set Theory

  • Author

    Wu, Chaozhong ; Lei, Hu ; Ma, Ming ; Yan, Xinping

  • Author_Institution
    Eng. Res. Center for Transp. Safety of MOE, Wuhan Univ. of Technol., Wuhan, China
  • Volume
    2
  • fYear
    2009
  • fDate
    6-7 June 2009
  • Firstpage
    59
  • Lastpage
    62
  • Abstract
    A single-vehicle crash is a typical pattern of traffic accidents and tends to cause heavy loss. The purpose of this study is to identify the factors significantly influencing single-vehicle crash injury severity, using a data selected from Beijing city for a 4-year period. Rough set theory was applied to complete the injury severity analysis, and followed by applying cross-validation method to estimate the prediction accuracy of extraction rules. Results show that it is effective for analyzing the severity of single-vehicle crashes with rough set theory.
  • Keywords
    road accidents; road safety; road traffic; road vehicles; rough set theory; vehicle dynamics; Beijing city; cross-validation method; extraction rule prediction; injury severity analysis; rough set theory; single-vehicle crash; traffic accident; Chaos; Computer crashes; Fuzzy set theory; Injuries; Road accidents; Road safety; Set theory; Transportation; Vehicle crash testing; Vehicle safety; cross-validation; rough sets; severity; single-vehicle crash; transportation safety;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Natural Computing, 2009. CINC '09. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3645-3
  • Type

    conf

  • DOI
    10.1109/CINC.2009.185
  • Filename
    5231033