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To reduce the conflict between online order acceptance and the charging behavior of electric taxis and to improve the operational efficiency of the taxi system, this paper proposes a joint scheduling scheme for the online order acceptance and charging behavior of electric taxis. A comprehensive vehicle operation simulation scenario is developed, incorporating taxis, charging stations, and orders as key components. The optimal scheduling scheme for the taxi system is determined using an improved genetic algorithm. The results show that, compared to the nearest pickup dispatch scheme, the proposed joint scheduling scheme increases the service time of taxis in the scenario while reducing cruising time and charging queue time. It optimizes vehicle operational states, improves the operational efficiency of charging stations, and enhances the quality of service for taxi orders. Furthermore, the improved algorithm significantly enhances the operational efficiency of the vehicle joint scheduling system compared to the traditional genetic algorithm.

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Enhancing Electric Taxi Operations: An Integrated Approach to Order Selection and Charging Decisions

  • 会议论文

  • 发表日期：

    2025年

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  • Yanxia Wang,
  • He Ding,
  • Haochen Hua,
  • Shaojun Gan,
  • Xin Wang

摘要

To reduce the conflict between online order acceptance and the charging behavior of electric taxis and to improve the operational efficiency of the taxi system, this paper proposes a joint scheduling scheme for the online order acceptance and charging behavior of electric taxis. A comprehensive vehicle operation simulation scenario is developed, incorporating taxis, charging stations, and orders as key components. The optimal scheduling scheme for the taxi system is determined using an improved genetic algorithm. The results show that, compared to the nearest pickup dispatch scheme, the proposed joint scheduling scheme increases the service time of taxis in the scenario while reducing cruising time and charging queue time. It optimizes vehicle operational states, improves the operational efficiency of charging stations, and enhances the quality of service for taxi orders. Furthermore, the improved algorithm significantly enhances the operational efficiency of the vehicle joint scheduling system compared to the traditional genetic algorithm.