Bi-Level Programming Approach for Optimal Charging Station Location and Traffic Assignment in Electric Autonomous Vehicle Systems

The increasing popularity of electric autonomous vehicles (EAVs) underscores the need for expanded en-route charging infrastructures to effectively support the widespread adoption of EAVs. This paper presents a bi-level program model for optimizing the placement of charging stations and traffic assignments within EAV systems. The upper-level model formulates a modified p-median problem to minimize the total flow-weighted distance for EAVs seeking to charge services by strategically locating charging stations in the transportation network. The lower-level model tackles the traffic assignment problem, aiming to minimize travel costs for EAVs considering stochastic charging demands. To solve the bi-level model, a customized heuristic iterative algorithm incorporating the Frank-Wolfe method is developed. A case study is conducted to demonstrate the feasibility and effectiveness of the proposed model. Furthermore, a sensitivity analysis is carried out to investigate the impact of variations in EAV users' value of time on charging station deployment.