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.


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    Title :

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


    Contributors:
    Hu, Run (author) / Tang, Zheyi (author) / Hu, Qinru (author) / Na, Xiaoxiang (author) / Angeloudis, Panagiotis (author) / Lee, Der-Horng (author) / Hu, Simon (author)


    Publication date :

    2023-09-24


    Size :

    948601 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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