• DocumentCode
    292057
  • Title

    Short-term traffic flow prediction models-a comparison of neural network and nonparametric regression approaches

  • Author

    Smith, Brian L. ; Demetsky, M.J.

  • Author_Institution
    Virginia Transp. Res. Council, VA, USA
  • Volume
    2
  • fYear
    1994
  • fDate
    2-5 Oct 1994
  • Firstpage
    1706
  • Abstract
    Traffic flow prediction models are expected to play an important role in intelligent vehicle highway systems. This paper demonstrate that the nearest neighbour models have the potential to serve as accurate and portable traffic flow prediction models. Furthermore the models have the advantages of being easily understood by field personnel
  • Keywords
    automated highways; forecasting theory; modelling; neural nets; nonparametric statistics; road traffic; traffic control; clustering model; intelligent vehicle highway systems; nearest neighbour models; neural network; nonparametric regression; traffic flow prediction models; Application software; Computational modeling; Databases; Decision making; Intelligent sensors; Intelligent transportation systems; Intelligent vehicles; Neural networks; Personnel; Predictive models; Road transportation; Telecommunication traffic; Traffic control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 1994. Humans, Information and Technology., 1994 IEEE International Conference on
  • Conference_Location
    San Antonio, TX
  • Print_ISBN
    0-7803-2129-4
  • Type

    conf

  • DOI
    10.1109/ICSMC.1994.400094
  • Filename
    400094