Spatio-Temporal Charging Availability Optimization for Electric Trucks: A perspective of hub strategies

Abstract For truck electrification, prioritizing high charging availability, which minimizes a driver’s total time cost including travel and waiting, is more critical than maximizing spatial accessibility. This study introduces a data-driven framework to optimize charging station placement for availability, using real-world Electronic Toll Collection (ETC) 2.0 trajectory data from Tokyo. Our multi-agent simulations model the competitive, self-interested behavior of drivers to minimize total time cost, which includes both travel and waiting periods. A key finding is the emergence of a hub-based strategy: the optimization process spontaneously clusters stations into high-capacity hubs to mitigate congestion. This emergent strategy significantly outperforms traditional accessibility-focused placements, achieving up to a 22.9% reduction in average time cost. This work provides strong evidence that policy for electric truck charging should shift from a dispersal strategy to one of strategic consolidation. Developing these efficient, high-availability hubs offers a more economically viable path to accelerate sustainable freight transport.