Current technology in traffic control is limited to a centralized approach that has not paid appropriate attention to efficiency of fuel consumption and is subject to the scale of transportation networks. This project proposes a transformative approach to the development of a distributed framework to reduce fuel consumption and travel time through the management of dynamic speed limit signs. The project proposes to integrate the roadway infrastructures equipped with sensing, communication, and parallel computation functionalities in the new traffic control paradigm. The research approach was built on three essential objectives to establish an energy-efficient traffic control methodology: (1) Implementation of a distributed control framework in large-scale transportation networks, (2) Simulation of dynamic traffic flow and performance tracking under implemented control signals using real-time traffic and vehicle data, (3) Data analysis and sustained strategy improvement. Going beyond the existing distributed architectures where precise dynamic flow models and fuel consumptions have not been considered, the work generated traffic control strategies to realize real-time, macroscopic-level traffic regulation with high precision. Simulation results demonstrated reduced fuel consumption and alleviated traffic congestion. The feasibility of the proposed optimization method was verified through Vissim simulation that considered different traffic volumes and random seed parameters.


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    Titel :

    Distributed Traffic Control for Reduced Fuel Consumption and Travel Time in Transportation Networks


    Beteiligte:
    Y. Zu (Autor:in) / C. Liu (Autor:in) / R. Dai (Autor:in) / A. Sharma (Autor:in) / J. Dong (Autor:in)

    Erscheinungsdatum :

    2018


    Format / Umfang :

    48 pages


    Medientyp :

    Report


    Format :

    Keine Angabe


    Sprache :

    Englisch