This study presents a path-based network equilibrium model for long-haul electric trucks (e-trucks), navigating the U.S. highway network. Emphasizing e-trucks' unique operational characteristics, the model, built on a background passenger car traffic, integrates essential travel costs, including travel and charging times, as well as mandated rest periods. The Method of Successive Averages (MSA) is utilized in our algorithm. A comparative analysis with conventional diesel trucks, using a streamlined version of the U.S. national highway network, reveals extended travel times for electric trucking, primarily due to charging requirements. Empirical findings show that e-trucks experience a significant increase in total travel time, about 55.9% more than their diesel counterparts. This delay, largely due to prolonged charging (including waiting) times, could potentially be offset through strategic infrastructure development and policy interventions.


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    Titel :

    Network Equilibrium Modeling for Long-Haul Electric Trucks


    Beteiligte:
    Cheng, Xi (Autor:in) / Lin, Jane (Autor:in)


    Erscheinungsdatum :

    26.02.2024


    Format / Umfang :

    575147 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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