IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v166y2022ics1366554522002630.html
   My bibliography  Save this article

Trajectory planning for autonomous modular vehicle docking and autonomous vehicle platooning operations

Author

Listed:
  • Li, Qianwen
  • Li, Xiaopeng

Abstract

Emerging autonomous modular vehicle (AMV) technology allows vehicle units to physically dock on or split from each other en route to form vehicles of different lengths. This technology has great potential in roadway logistics where platoons/long trains are formed to transport goods and passengers, i.e., freight and transit systems. AMV docking is an extreme case of autonomous vehicle (AV) platooning in that AMVs are physically connected with zero gaps. This paper formulates the AMV docking and AV platooning trajectory planning problem into a two-stage optimization problem. A feasible cone method is proposed to reveal the theoretical properties of solution feasibility and solve the first-stage problem analytically. This method provides the basics for a parsimonious heuristic approach to design trajectories specified as several quadratic segments. A heuristic alternative solution based on Pontryagin's maximum principle is proposed to solve a special case of the original problem to the exact optimum. Then an exact solution approach based on quadratic programming is proposed to optimize the trajectories. The feasible cone method is used to construct valid cuts to expedite the exact solution efficiency. Numerical experiments show that the parsimonious heuristic approach can achieve near-optimal solutions and greatly reduce the solution time compared with the exact solution approach, appealing to real-time engineering applications. The results also demonstrate the superiority of the parsimonious heuristic approach in optimizing AMV docking and AV platooning trajectories compared with traditional platooning methods. Sensitivity analysis results shed insights into advising parameter selections of platoon-related logistics to balance the tradeoff between operational efficiency and cost.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:transe:v:166:y:2022:i:c:s1366554522002630
    DOI: 10.1016/j.tre.2022.102886
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554522002630
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tre.2022.102886?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Noruzoliaee, Mohamadhossein & Zou, Bo & Zhou, Yan (Joann), 2021. "Truck platooning in the U.S. national road network: A system-level modeling approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    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. Li, Li & Li, Xiaopeng, 2019. "Parsimonious trajectory design of connected automated traffic," Transportation Research Part B: Methodological, Elsevier, vol. 119(C), pages 1-21.
    5. Zhang, Wei & Jenelius, Erik & Ma, Xiaoliang, 2017. "Freight transport platoon coordination and departure time scheduling under travel time uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 98(C), pages 1-23.
    6. Larsen, Rune & Rich, Jeppe & Rasmussen, Thomas Kjær, 2019. "Hub-based truck platooning: Potentials and profitability," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 249-264.
    7. Wei, Yuguang & Avcı, Cafer & Liu, Jiangtao & Belezamo, Baloka & Aydın, Nizamettin & Li, Pengfei(Taylor) & Zhou, Xuesong, 2017. "Dynamic programming-based multi-vehicle longitudinal trajectory optimization with simplified car following models," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 102-129.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Qiu, Jiahua & Du, Lili, 2023. "Cooperative trajectory control for synchronizing the movement of two connected and autonomous vehicles separated in a mixed traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 174(C).

    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. 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.
    2. Hu, Qiaolin & Gu, Weihua & Wu, Lingxiao & Zhang, Le, 2024. "Optimal autonomous truck platooning with detours, nonlinear costs, and a platoon size constraint," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 186(C).
    3. Liatsos, Vasileios & Golias, Mihalis & Hourdos, John & Mishra, Sabyasachee, 2024. "The capacitated hybrid truck platooning network design problem," Transportation Research Part A: Policy and Practice, Elsevier, vol. 181(C).
    4. Barua, Limon & Zou, Bo & Choobchian, Pooria, 2023. "Maximizing truck platooning participation with preferences," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).
    5. 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).
    6. Noruzoliaee, Mohamadhossein & Zou, Bo & Zhou, Yan (Joann), 2021. "Truck platooning in the U.S. national road network: A system-level modeling approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    7. Sindi, Safaa & Woodman, Roger, 2021. "Implementing commercial autonomous road haulage in freight operations: An industry perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 152(C), pages 235-253.
    8. Lu, Gongyuan & Nie, Yu(Marco) & Liu, Xiaobo & Li, Denghui, 2019. "Trajectory-based traffic management inside an autonomous vehicle zone," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 76-98.
    9. Zou, Kaijie & Zhang, Ke & Li, Meng, 2024. "Operational design for modular electrified transit in corridor areas," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 187(C).
    10. 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.
    11. Xiong, Xi & Sha, Junyi & Jin, Li, 2021. "Optimizing coordinated vehicle platooning: An analytical approach based on stochastic dynamic programming," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 482-502.
    12. Chen, Shukai & Wang, Hua & Meng, Qiang, 2021. "Autonomous truck scheduling for container transshipment between two seaport terminals considering platooning and speed optimization," Transportation Research Part B: Methodological, Elsevier, vol. 154(C), pages 289-315.
    13. Boshuai Zhao & Roel Leus, 2022. "An improved decomposition-based heuristic for truck platooning," Papers 2210.05562, arXiv.org, revised Feb 2023.
    14. 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).
    15. Xue, Zhaojie & Lin, Hui & You, Jintao, 2021. "Local container drayage problem with truck platooning mode," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    16. 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).
    17. Bouchery, Yann & Hezarkhani, Behzad & Stauffer, Gautier, 2022. "Coalition formation and cost sharing for truck platooning," Transportation Research Part B: Methodological, Elsevier, vol. 165(C), pages 15-34.
    18. Gong, Siyuan & Du, Lili, 2018. "Cooperative platoon control for a mixed traffic flow including human drive vehicles and connected and autonomous vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 116(C), pages 25-61.
    19. Zhang, Yongxiang & Peng, Qiyuan & Yao, Yu & Zhang, Xin & Zhou, Xuesong, 2019. "Solving cyclic train timetabling problem through model reformulation: Extended time-space network construct and Alternating Direction Method of Multipliers methods," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 344-379.
    20. Lee, Enoch & Cen, Xuekai & Lo, Hong K., 2022. "Scheduling zonal-based flexible bus service under dynamic stochastic demand and Time-dependent travel time," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).

    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:eee:transe:v:166:y:2022:i:c:s1366554522002630. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description .

    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.