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Optimal Vehicle Scheduling and Charging Infrastructure Planning for Autonomous Modular Transit System

Author

Listed:
  • Ande Chang

    (College of Forensic Sciences, Criminal Investigation Police University of China, Shenyang 110035, China)

  • Yuan Cong

    (School of Transportation, Jilin University, Changchun 130022, China)

  • Chunguang Wang

    (State Key Laboratory for Strength and Vibration of Mechanical Structures, School of Aerospace Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

  • Yiming Bie

    (School of Transportation, Jilin University, Changchun 130022, China)

Abstract

Prioritizing the development of public transport is an effective way to improve the sustainability of the transport system. In recent years, bus passenger flow has been declining in many cities. How to reform the operating mode of the public transportation system is an important issue that needs to be solved. An autonomous modular bus (AMB) is capable of physical coupling and uncoupling to flexibly adjust vehicle capacity as well as provide high-quality service under unbalanced passenger demand conditions. To promote AMB adoption and reduce the operating cost of the bus route, this paper presents a joint optimization method to simultaneously determine the AMB dispatching plan, charging plan, and charging infrastructure configuration scheme. Then, a mixed-integer programming model is formulated to minimize the operating costs of the bus route. A hybrid intelligent algorithm combining enumeration, cloning algorithm, and particle swarm optimization algorithm is designed to resolve the formulated model. Subsequently, an actual bus route is taken as an example to validate the proposed method. Results indicate that the developed method in this paper can reduce the operating costs and operational energy consumption of the route compared with the real route operating plan. Specifically, the reduction ratio of the former is 23.85%, and the reduction ratio of the latter is 5.92%. The results of this study validate the feasibility and advantages of autonomous modular transit service, contributing positively to the sustainable development of the urban public transportation system.

Suggested Citation

  • Ande Chang & Yuan Cong & Chunguang Wang & Yiming Bie, 2024. "Optimal Vehicle Scheduling and Charging Infrastructure Planning for Autonomous Modular Transit System," Sustainability, MDPI, vol. 16(8), pages 1-16, April.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:8:p:3316-:d:1376342
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    References listed on IDEAS

    as
    1. Chen, Zhiwei & Li, Xiaopeng & Zhou, Xuesong, 2020. "Operational design for shuttle systems with modular vehicles under oversaturated traffic: Continuous modeling method," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 76-100.
    2. Dakic, Igor & Yang, Kaidi & Menendez, Monica & Chow, Joseph Y.J., 2021. "On the design of an optimal flexible bus dispatching system with modular bus units: Using the three-dimensional macroscopic fundamental diagram," Transportation Research Part B: Methodological, Elsevier, vol. 148(C), pages 38-59.
    3. Chen, Zhiwei & Li, Xiaopeng & Zhou, Xuesong, 2019. "Operational design for shuttle systems with modular vehicles under oversaturated traffic: Discrete modeling method," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 1-19.
    4. Perumal, Shyam S.G. & Lusby, Richard M. & Larsen, Jesper, 2022. "Electric bus planning & scheduling: A review of related problems and methodologies," European Journal of Operational Research, Elsevier, vol. 301(2), pages 395-413.
    5. Gang Chen & Dawei Hu & Steven Chien & Lei Guo & Mingzheng Liu, 2020. "Optimizing Wireless Charging Locations for Battery Electric Bus Transit with a Genetic Algorithm," Sustainability, MDPI, vol. 12(21), pages 1-20, October.
    6. Ke, Bwo-Ren & Chung, Chen-Yuan & Chen, Yen-Chang, 2016. "Minimizing the costs of constructing an all plug-in electric bus transportation system: A case study in Penghu," Applied Energy, Elsevier, vol. 177(C), pages 649-660.
    7. Liu, Xiaohan & Qu, Xiaobo & Ma, Xiaolei, 2021. "Improving flex-route transit services with modular autonomous vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    8. Li, Qianwen & Li, Xiaopeng, 2023. "Trajectory optimization for autonomous modular vehicle or platooned autonomous vehicle split operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 176(C).
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