Existing adaptive traffic signal control (ATSC) systems rely on dedicated fixed-point sensors, such as inductive loop detectors or video cameras, for measuring traffic demands and discharge saturation flow rates. The cost associated with installation, operation, and maintenance of these sensors is one of the factors that limit the deployment of ATSCs. The emergence of connected vehicles (CVs), which continuously broadcast their speed, position, heading, and other information to other vehicles and to roadside infrastructure, provides an opportunity to reduce the reliance of ATSC on data from fixed sensors and potentially to reduce ATSC deployment costs. However, so that existing ATSC systems can operate by using CV data, a methodology is needed for estimating demands and saturation flow rate based on CV data instead of fixed sensor data. This paper focuses on estimating the time-varying saturation flow rate for individual lane groups at signalized intersections solely on the basis of CV data. The accuracy of a proposed methodology is quantified through microsimulation for a range of traffic conditions, lane group configurations, and levels of market penetration (LMP) of CVs. The analysis shows that the proposed methodology can capture temporal variations in the saturation flow rate caused by road incidents, queues spilling back from downstream bottlenecks, and lane closures. The evaluation results show that the mean absolute relative error of the lane group saturation flow rate ranged from approximately 2% to 9% when LMP = 20% and only 1% to 2% when LMP = 100%.


    Zugriff

    Download

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Real-Time Estimation of Saturation flow Rates for Dynamic Traffic Signal Control using Connected-Vehicle Data


    Weitere Titelangaben:

    Transportation Research Record


    Beteiligte:
    Bagheri, Ehsan (Autor:in) / Mehran, Babak (Autor:in) / Hellinga, Bruce (Autor:in)


    Erscheinungsdatum :

    2019-04-04




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    A Real-time Traffic Signal Control Strategy Under Partially Connected Vehicle Environment

    Kancharla Kamal Keerthi Chandan / Álvaro Jorge Maia Seco / Ana Maria César Bastos Silva | DOAJ | 2019

    Freier Zugriff

    A Real-time Traffic Signal Control Strategy Under Partially Connected Vehicle Environment

    Kamal Keerthi Chandan, Kancharla / Jorge Maia Seco, Álvaro / Maria César Bastos Silva, Ana | BASE | 2019

    Freier Zugriff

    A real-time network-level traffic signal control methodology with partial connected vehicle information

    Islam, S.M.A. Bin Al / Hajbabaie, Ali / Aziz, H.M. Abdul | Elsevier | 2020


    Real-Time Traffic State Estimation With Connected Vehicles

    Khan, Sakib Mahmud | Online Contents | 2017


    Real-Time Traffic State Estimation With Connected Vehicles

    Khan, Sakib Mahmud / Dey, Kakan C. / Chowdhury, Mashrur | IEEE | 2017