Connected and autonomous vehicles (CAV) are becoming more integrated with traffic signal infrastructure for V2I applications, such as traffic light indication and automated driving. However, modern traffic signal controllers allocate green time using vehicle sensors and therefore the anticipated green time has significant stochastic variation. This study develops a methodology to characterize green time stochastic variation for actuated-coordinated operation. During the peak hours where the demand was highly consistent, green intervals can be predicted with high certainty. In contrast, during midday and late evening, stochastic variation increased significantly due to the varying arrival patterns and associated real-time responsiveness of the traffic signal controller. The statistical characterization methods presented in this paper are important for green light optimized speed advisory (GLOSA) and eco-driving, technologies that rely on having an accurate estimate of the beginning of green (BOG) and end of green (EOG). Prior knowledge on typical values of how early to stop or shutdown the vehicles at a traffic signal approach can significantly improve efficiency and manage emissions for CAV. The paper concludes with a proposed graphical performance measure chart that can be used by traffic engineers and automotive vendors to frame the discussion on traffic signal operation.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Signal Green Time Estimation Method for Connected Vehicle-to-Infrastructure Applications


    Beteiligte:
    Mathew, Jijo K. (Autor:in) / Li, Howell (Autor:in) / Bullock, Darcy M. (Autor:in)


    Erscheinungsdatum :

    2019-11-01


    Format / Umfang :

    1204722 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Data Infrastructure for Connected Vehicle Applications

    Wang, Xingmin / Shen, Shengyin / Bezzina, Debra et al. | Transportation Research Record | 2020


    VIRTUAL CONNECTED VEHICLE INFRASTRUCTURE

    ZLOTKIN GILAD / LELCUK ALON | Europäisches Patentamt | 2023

    Freier Zugriff

    VIRTUAL CONNECTED VEHICLE INFRASTRUCTURE

    ZLOTKIN GILAD / LELCUK ALON | Europäisches Patentamt | 2020

    Freier Zugriff

    Virtual connected vehicle infrastructure

    ZLOTKIN GILAD / LELCUK ALON | Europäisches Patentamt | 2022

    Freier Zugriff

    VIRTUAL CONNECTED VEHICLE INFRASTRUCTURE

    ZLOTKIN GILAD / LELCUK ALON | Europäisches Patentamt | 2021

    Freier Zugriff