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.
Network Equilibrium Modeling for Long-Haul Electric Trucks
26.02.2024
575147 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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