In this paper, we use the Perceived Safety Analysis Framework (PSAF) to assess the awareness of vehicles performing an unprotected left turn at unsignalized intersections. PSAF is an analytical method developed to quantify the awareness of vehicles to surrounding safety-critical road users in traffic. We derive safety conditions for unprotected left turns using surrogate safety measures and right of way rules, and determine which road users are safety-critical to the left-turning ego vehicle. Then, we evaluate the Perceived Safety Error based on whether the ego vehicle can detect critical road users (CRUs) using sensors (such as camera or radar) and via vehicle-to-everything (V2X) communication. We demonstrate that for intersections with sparse traffic, vehicle-to-vehicle (V2V) communication may be insufficient for left-turning vehicles to get full awareness of CRUs, and vehicle-to-infrastructure (V2I) communication helps to eliminate awareness gaps.


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    Titel :

    On the Awareness of Connected Vehicles at Unsignalized Intersections


    Beteiligte:


    Erscheinungsdatum :

    01.06.2022


    Format / Umfang :

    1913885 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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