This article presents an intersection control strategy involving a mix of connected and autonomous vehicles (CAV) and human-driven vehicles (HDV). A queue length-based priority strategy for multilane unsignalized intersections using calibrated microscopic traffic simulation is proposed in the article. In the strategy, the right of way of a CAV is given according to the waiting queue of its lane. The strategy was implemented at a three-lane four-leg intersection, and its efficiency was compared with that of the conventional fixed signal strategy. The queue length-based priority strategy with fixed and dynamic traffic signal strategies is also extensively compared. The strategy involves not only the idea of responding to the queue but also incorporates vehicles-to-everything (V2X) behaviors into the calculation. The total traffic time graphs of each strategy show that the priority strategy significantly reduces the delay compared to fixed or dynamic traffic signals. The proposed strategy has the potential for application in future road environments and improvements because the effects vary with the increase in CAVs. New criteria for removing traffic signals is also suggested by comparing the intersection control strategies for which total travel time can be reduced by a maximum 25.4% according to the increase in the CAV market penetration rates. The safety indicators among strategies are also compared to ensure that the proposed strategy is applicable to mixed traffic intersections.


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    Titel :

    Queue Length-Based Priority Strategy for Unsignalized Intersections in Mixed-Traffic Environments


    Beteiligte:
    Kim, Brian Young-Hwan (Autor:in) / Joo, Yang-Jun (Autor:in) / Choi, Junhee (Autor:in) / Kim, Dong-Kyu (Autor:in)


    Erscheinungsdatum :

    01.09.2025




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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