IDEAS home Printed from https://ideas.repec.org/a/inm/orijoc/v35y2023i6p1242-1260.html
   My bibliography  Save this article

Platoon Optimization Based on Truck Pairs

Author

Listed:
  • Anirudh Kishore Bhoopalam

    (Rotterdam School of Management, Erasmus University, 3062 PA Rotterdam, Netherlands)

  • Niels Agatz

    (Rotterdam School of Management, Erasmus University, 3062 PA Rotterdam, Netherlands)

  • Rob Zuidwijk

    (Rotterdam School of Management, Erasmus University, 3062 PA Rotterdam, Netherlands)

Abstract

Truck platooning technology allows trucks to drive at short headways to save fuel and associated emissions. However, fuel savings from platooning are relatively small, so forming platoons should be convenient and associated with minimum detours and delays. In this paper, we focus on developing optimization technology to form truck platoons. We formulate a mathematical program for the platoon routing problem with time windows (PRP-TW) based on a time–space network. We provide polynomial-time algorithms to solve special cases of PRP-TW with two-truck platoons. Based on these special cases, we build several fast heuristics. An extensive set of numerical experiments shows that our heuristics perform well. Moreover, we show that simple two-truck platoons already capture most of the potential savings of platooning.

Suggested Citation

  • Anirudh Kishore Bhoopalam & Niels Agatz & Rob Zuidwijk, 2023. "Platoon Optimization Based on Truck Pairs," INFORMS Journal on Computing, INFORMS, vol. 35(6), pages 1242-1260, November.
  • Handle: RePEc:inm:orijoc:v:35:y:2023:i:6:p:1242-1260
    DOI: 10.1287/ijoc.2020.0302
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/ijoc.2020.0302
    Download Restriction: no

    File URL: https://libkey.io/10.1287/ijoc.2020.0302?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
    ---><---

    References listed on IDEAS

    as
    1. Hani S. Mahmassani, 2016. "50th Anniversary Invited Article—Autonomous Vehicles and Connected Vehicle Systems: Flow and Operations Considerations," Transportation Science, INFORMS, vol. 50(4), pages 1140-1162, November.
    2. Natashia Boland & Mike Hewitt & Luke Marshall & Martin Savelsbergh, 2017. "The Continuous-Time Service Network Design Problem," Operations Research, INFORMS, vol. 65(5), pages 1303-1321, October.
    3. Nowakowski, Christopher & Shladover, Steven E & Lu, Xiao-Yun & Thompson, Deborah & Kailas, Aravind, 2015. "Cooperative Adaptive Cruise Control (CACC) for Truck Platooning: Operational Concept Alternatives," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt7jf9n5wm, Institute of Transportation Studies, UC Berkeley.
    4. 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.
    5. George B. Dantzig, 1960. "On the Shortest Route Through a Network," Management Science, INFORMS, vol. 6(2), pages 187-190, January.
    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.
    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. Kishore Bhoopalam, A. & Agatz, N.A.H. & Zuidwijk, R.A., 2020. "Spatial and Temporal Synchronization of Truck Platoons," ERIM Report Series Research in Management ERS-2020-014-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    2. Hao, Yilang & Chen, Zhibin & Sun, Xiaotong & Tong, Lu, 2025. "Planning of truck platooning for road-network capacitated vehicle routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 194(C).
    3. 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.
    4. 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.
    5. Sun, Xiaotong & Yin, Yafeng, 2021. "Decentralized game-theoretical approaches for behaviorally-stable and efficient vehicle platooning," Transportation Research Part B: Methodological, Elsevier, vol. 153(C), pages 45-69.
    6. 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.
    7. 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).
    8. 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).
    9. 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).
    10. 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).
    11. Bhoopalam, Anirudh Kishore & Agatz, Niels & Zuidwijk, Rob, 2018. "Planning of truck platoons: A literature review and directions for future research," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 212-228.
    12. 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.
    13. 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).
    14. Scherr, Yannick Oskar & Hewitt, Mike & Neumann Saavedra, Bruno Albert & Mattfeld, Dirk Christian, 2020. "Dynamic discretization discovery for the service network design problem with mixed autonomous fleets," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 164-195.
    15. Scherr, Yannick Oskar & Neumann Saavedra, Bruno Albert & Hewitt, Mike & Mattfeld, Dirk Christian, 2019. "Service network design with mixed autonomous fleets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 124(C), pages 40-55.
    16. Boshuai Zhao & Roel Leus, 2022. "An improved decomposition-based heuristic for truck platooning," Papers 2210.05562, arXiv.org, revised Feb 2023.
    17. Kishore Bhoopalam, A. & Agatz, N.A.H. & Zuidwijk, R.A., 2017. "Planning of Truck Platoons: a Literature Review and Directions for Future Research," ERIM Report Series Research in Management ERS-2017-010-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    18. de Lima, Vinícius L. & Alves, Cláudio & Clautiaux, François & Iori, Manuel & Valério de Carvalho, José M., 2022. "Arc flow formulations based on dynamic programming: Theoretical foundations and applications," European Journal of Operational Research, Elsevier, vol. 296(1), pages 3-21.
    19. Zhang, Fang & Lu, Jian & Hu, Xiaojian & Meng, Qiang, 2023. "Integrated deployment of dedicated lane and roadside unit considering uncertain road capacity under the mixed-autonomy traffic environment," Transportation Research Part B: Methodological, Elsevier, vol. 174(C).
    20. Wu, Guohong & Wu, Jiaming & Zheng, Shiteng & Jiang, Rui, 2024. "Managing merging from a dedicated CAV lane into a conventional lane considering the stochasticity of connected human-driven vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 652(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:inm:orijoc:v:35:y:2023:i:6:p:1242-1260. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.