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The identical-path truck platooning problem

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  • Boysen, Nils
  • Briskorn, Dirk
  • Schwerdfeger, Stefan

Abstract

Platooning has been identified as a promising way to reduce the carbon footprint and fuel consumption of freight transportation. Recent technological developments connecting a platoon via digital data transmission even allow that the driver of the front truck controls all (unmanned) follower vehicles. Existing research mainly focuses on the technological and safety aspects of controlling the trucks and their distances. However, the efficiency of platooning is not only dependent on the aerodynamic drag, which considerably reduces with decreasing inter-vehicle distance; it is also influenced by the platoon formation process. To explore the impact of this and other neglected aspects on the efficiency of platooning (i.e., the diffusion of platooning technology, maximum platoon lengths, and the trucks’ willingness-to-wait for partners) a basic scheduling problem for the platoon building process along a single path is investigated. By differentiating problem characteristics, e.g., the objective function, we derive different problem settings for which a detailed analysis of computational complexity is provided. Efficient algorithms are derived and applied to explore the impact of the diffusion of platooning technology, the maximum platoon length, and the tightness of time windows. Our results show that these factors can considerably reduce the positive effects of truck platooning, and, thus, the benefit may diminish.

Suggested Citation

  • Boysen, Nils & Briskorn, Dirk & Schwerdfeger, Stefan, 2018. "The identical-path truck platooning problem," Transportation Research Part B: Methodological, Elsevier, vol. 109(C), pages 26-39.
    • Handle: RePEc:eee:transb:v:109:y:2018:i:c:p:26-39
    DOI: 10.1016/j.trb.2018.01.006
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    References listed on IDEAS

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    Cited by:

    1. Schwerdfeger, Stefan & Otto, Alena & Boysen, Nils, 2021. "Rail platooning: Scheduling trains along a rail corridor with rapid-shunting facilities," European Journal of Operational Research, Elsevier, vol. 294(2), pages 760-778.
    2. Huailei Cheng & Yuhong Wang & Dan Chong & Chao Xia & Lijun Sun & Jenny Liu & Kun Gao & Ruikang Yang & Tian Jin, 2023. "Truck platooning reshapes greenhouse gas emissions of the integrated vehicle-road infrastructure system," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    3. Ramirez Ibarra, Monica & Saphores, Jean-Daniel M., 2023. "1,000 HP electric drayage trucks as a substitute for new freeway lanes construction," Transportation Research Part A: Policy and Practice, Elsevier, vol. 171(C).
    4. 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.
    5. Scholl, Joachim & Boysen, Nils & Scholl, Armin, 2023. "E-platooning: Optimizing platoon formation for long-haul transportation with electric commercial vehicles," European Journal of Operational Research, Elsevier, vol. 304(2), pages 525-542.
    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. I. de Zarzà & J. de Curtò & Juan Carlos Cano & Carlos T. Calafate, 2023. "Drone-Based Decentralized Truck Platooning with UWB Sensing and Control," Mathematics, MDPI, vol. 11(22), pages 1-22, November.
    8. You, Jintao & Miao, Lixin & Zhang, Canrong & Xue, Zhaojie, 2020. "A generic model for the local container drayage problem using the emerging truck platooning operation mode," Transportation Research Part B: Methodological, Elsevier, vol. 133(C), pages 181-209.
    9. 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.
    10. Vitalii Naumov & Olha Shulika & Oleksandra Orda & Hanna Vasiutina & Marek Bauer & Myroslav Oliskevych, 2022. "Shaping the Optimal Technology for Servicing the Long-Distance Deliveries of Packaged Cargo by Road Transport," Sustainability, MDPI, vol. 14(12), pages 1-17, June.
    11. 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).
    12. 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).
    13. You, Jintao & Wang, Yuan & Xue, Zhaojie, 2023. "An exact algorithm for the multi-trip container drayage problem with truck platooning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    14. Abdolmaleki, Mojtaba & Shahabi, Mehrdad & Yin, Yafeng & Masoud, Neda, 2021. "Itinerary planning for cooperative truck platooning," Transportation Research Part B: Methodological, Elsevier, vol. 153(C), pages 91-110.
    15. 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.
    16. 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).
    17. Wu, Pei-Yang & Guo, Ren-Yong & Lin, Zhiyuan & Liu, Ronghui & Xu, Pu, 2024. "Improving passenger travel efficiency through a dynamic autonomous non-stop rail transit system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 182(C).
    18. 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.
    19. 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.
    20. Boshuai Zhao & Roel Leus, 2022. "An improved decomposition-based heuristic for truck platooning," Papers 2210.05562, arXiv.org, revised Feb 2023.
    21. Shailesh Chandra & Timothy Thai, 2022. "Analyzing Freight Truck Platoon Accessibility with Route Deviations," Sustainability, MDPI, vol. 14(4), pages 1-22, February.
    22. 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).
    23. 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).

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