Vehicular Ad Hoc Networks (VANETs) represent a significant leap forward in the deployment of intelligent transport systems. These networks enable vehicles to instantly exchange traffic information with the aim of smoothing traffic flows and intensifying drivers comfort. In this context, this study addresses the issue of traffic congestion description and detection in multi-lane highways. By making use of collected information, a Markov chain based mobility model is proposed to predict the future road traffic states. Based on the obtained stationary distribution probabilities, performance criteria in steady-state are inferred and computed for different road configurations. The numerical results validate the model demonstrated in the paper.


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    Titel :

    A Stochastic Traffic Model for Congestion Detection in Multi-lane Highways


    Weitere Titelangaben:

    Lect.Notes Social.Inform.


    Beteiligte:
    Foschini, Luca (Herausgeber:in) / El Kamili, Mohamed (Herausgeber:in) / Oumaima, El Joubari (Autor:in) / Jalel, Ben Othman (Autor:in) / Véronique, Vèque (Autor:in)

    Kongress:

    International Conference on Ad Hoc Networks ; 2020 ; Paris, France November 17, 2020 - November 17, 2020



    Erscheinungsdatum :

    31.01.2021


    Format / Umfang :

    13 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch