IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i8p3316-d1376342.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/8/3316/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/8/3316/
    Download Restriction: no
    ---><---

    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. 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.
    3. 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).
    4. 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.
    5. 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).
    6. 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.
    7. 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.
    8. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Jiyu & Ge, Ying-En & Tang, Chunyan & Zhong, Meisu, 2024. "Optimising modular-autonomous-vehicle transit service employing coupling–decoupling operations plus skip-stop strategy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 184(C).
    2. Kuo, Yong-Hong & Leung, Janny M.Y. & Yan, Yimo, 2023. "Public transport for smart cities: Recent innovations and future challenges," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1001-1026.
    3. Tian, Qingyun & Wang, David Z.W. & Lin, Yun Hui, 2022. "Optimal deployment of autonomous buses into a transit service network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).
    4. Gong, Manlin & Hu, Yucong & Chen, Zhiwei & Li, Xiaopeng, 2021. "Transfer-based customized modular bus system design with passenger-route assignment optimization," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
    5. Hatzenbühler, Jonas & Jenelius, Erik & Gidófalvi, Gyözö & Cats, Oded, 2023. "Modular vehicle routing for combined passenger and freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    6. Foda, Ahmed & Abdelaty, Hatem & Mohamed, Moataz & El-Saadany, Ehab, 2023. "A generic cost-utility-emission optimization for electric bus transit infrastructure planning and charging scheduling," Energy, Elsevier, vol. 277(C).
    7. 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.
    8. Chen, Zhiwei & Li, Xiaopeng, 2021. "Designing corridor systems with modular autonomous vehicles enabling station-wise docking: Discrete modeling method," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    9. Li, Qianwen & Li, Xiaopeng, 2022. "Trajectory planning for autonomous modular vehicle docking and autonomous vehicle platooning operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 166(C).
    10. Xuemei Zhou & Guohui Wei & Yunbo Zhang & Qianlin Wang & Huanwu Guo, 2023. "Optimizing Multi-Vehicle Demand-Responsive Bus Dispatching: A Real-Time Reservation-Based Approach," Sustainability, MDPI, vol. 15(7), pages 1-18, March.
    11. Chen, Shukai & Wang, Hua & Meng, Qiang, 2023. "Cost allocation of cooperative autonomous truck platooning: Efficiency and stability analysis," Transportation Research Part B: Methodological, Elsevier, vol. 173(C), pages 119-141.
    12. Zhang, Zhenhao & Tafreshian, Amirmahdi & Masoud, Neda, 2020. "Modular transit: Using autonomy and modularity to improve performance in public transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    13. Manzolli, Jônatas Augusto & Trovão, João Pedro & Antunes, Carlos Henggeler, 2022. "A review of electric bus vehicles research topics – Methods and trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    14. Wu, Jiaming & Kulcsár, Balázs & Selpi, & Qu, Xiaobo, 2021. "A modular, adaptive, and autonomous transit system (MAATS): A in-motion transfer strategy and performance evaluation in urban grid transit networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 151(C), pages 81-98.
    15. Yiming Bie & Mingjie Hao & Mengzhu Guo, 2021. "Optimal Electric Bus Scheduling Based on the Combination of All-Stop and Short-Turning Strategies," Sustainability, MDPI, vol. 13(4), pages 1-21, February.
    16. Pei, Mingyang & Lin, Peiqun & Du, Jun & Li, Xiaopeng & Chen, Zhiwei, 2021. "Vehicle dispatching in modular transit networks: A mixed-integer nonlinear programming model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    17. Boud Verbrugge & Mohammed Mahedi Hasan & Haaris Rasool & Thomas Geury & Mohamed El Baghdadi & Omar Hegazy, 2021. "Smart Integration of Electric Buses in Cities: A Technological Review," Sustainability, MDPI, vol. 13(21), pages 1-23, November.
    18. Yueqiu Wu & Liping Wang & Yanke Zhang & Jiajie Wu & Qiumei Ma & Lisha Yue, 2021. "Application of Marginal Rate of Transformation in Decision Making of Multi-Objective Reservoir Optimal Operation Scheme," Sustainability, MDPI, vol. 13(3), pages 1-17, February.
    19. Olayiwola Alatise & Arkadeep Deb & Erfan Bashar & Jose Ortiz Gonzalez & Saeed Jahdi & Walid Issa, 2023. "A Review of Power Electronic Devices for Heavy Goods Vehicles Electrification: Performance and Reliability," Energies, MDPI, vol. 16(11), pages 1-25, May.
    20. Sun, Hao & Yang, Jun & Yang, Chao, 2019. "A robust optimization approach to multi-interval location-inventory and recharging planning for electric vehicles," Omega, Elsevier, vol. 86(C), pages 59-75.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:8:p:3316-:d:1376342. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.