• DocumentCode
    3151473
  • Title

    Modeling traffic system complexity through fuzzy entropy

  • Author

    Hoogendoorn, R. ; van Arem, Bart

  • Author_Institution
    Fac. Civil Eng. & Geosci., Delft Univ. of Technol., Delft, Netherlands
  • fYear
    2013
  • fDate
    6-9 Oct. 2013
  • Firstpage
    540
  • Lastpage
    546
  • Abstract
    Cooperative traffic management may have beneficial effects on society. However, the efficiency of the measures are largely dependent on behavior of the road users. The application of these measures may be assumed to have an influence on complexity of the driving conditions, with in turn an influence on behavior. Mathematical models of driving behavior incorporated in microscopic simulation software packages are currently inadequate to capture this influence. In order to adequately incorporate this influence an empirically underpinned quantification of the complexity of the driving conditions is needed. In this contribution we take some first steps towards the development of a quantification of traffic system complexity using fuzzy entropy. We present the proposed method and show the workings of the method using a case study. The contribution finishes with a discussion section and recommendations for future research.
  • Keywords
    entropy; fuzzy set theory; road traffic; cooperative traffic management; driving behavior; driving conditions complexity; fuzzy entropy; mathematical models; road users behavior; traffic system complexity modeling; traffic system complexity quantification; Complexity theory; Context; Entropy; Mathematical model; Roads; Uncertainty; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Transportation Systems - (ITSC), 2013 16th International IEEE Conference on
  • Conference_Location
    The Hague
  • Type

    conf

  • DOI
    10.1109/ITSC.2013.6728287
  • Filename
    6728287