Network Equilibrium Modeling for Long-Haul Electric Trucks

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.