Short-term vehicular traffic parameter forecasting is essential for vehicular traffic related applications and research. Many route choice models have been proposed based on travel time as a decision factor. Most efforts have gone into developing suitable methodologies for modeling of vehicular traffic parameters and predict anticipated traffic conditions. Researchers have used single point data collections at highway and univariate statistical models in anticipation of vehicular traffic parameters. Recent development of technologies in the form of Internet of Things (IOT) allows researchers to focus on an under explored research area of vehicular traffic parameter forecasting. The paper discusses about challenges for parameters of short-term vehicular traffic forecasting.


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    Titel :

    Review of Challenges for Short-Term Vehicular Traffic Forecasting


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Patil, Varsha H. (Herausgeber:in) / Dey, Nilanjan (Herausgeber:in) / N. Mahalle, Parikshit (Herausgeber:in) / Shafi Pathan, Mohd (Herausgeber:in) / Kimbahune, Vinod. V. (Herausgeber:in) / Khairnar, Hitendra S. (Autor:in) / Sonkamble, B. A. (Autor:in)


    Erscheinungsdatum :

    2021-03-19


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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