The next generation of wireless technology, 5G, provides an opportunity to intensify the application of connected transportation systems. Connectivity based on long-range communication that allows for the transmission of massive amounts of data in near real-time can enhance transportation system efficiency and safety. This study focuses on the optimal lane selection (OLS) algorithm proposed in [1] as one possible connected vehicle application. This application was proposed to provide a driver with optimal lane advisories, as estimated based on downstream data transmitted through short-range wireless communication. This study enhances the OLS in consideration of long-range connectivity. The developed OLS application was evaluated on a freeway segment using a microscopic traffic simulator, INTEGRATION. Based on a sensitivity analysis of the traffic demand level, the OLS algorithm was demonstrated to be beneficial at demand levels between 75% and 100% of capacity and also improved lane allocation performance. The proposed application was also evaluated on a section of I-66 in the USA. The results show that the OLS application can not only reduce delay and travel time of connected vehicles, but also produce system-wide benefits.


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    Titel :

    Development and Testing of a Connected Vehicle Optimal Lane Selection Algorithm


    Beteiligte:
    Kang, Kyungwon (Autor:in) / Bichiou, Youssef (Autor:in) / Rakha, Hesham A. (Autor:in) / Elbery, Ahmed (Autor:in) / Yang, Hao (Autor:in)


    Erscheinungsdatum :

    2019-10-01


    Format / Umfang :

    660473 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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    IMPROVING TRAFFIC OPERATIONS USING REAL-TIME OPTIMAL LANE SELECTION WITH CONNECTED VEHICLE TECHNOLOGY

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