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Itinerary planning for cooperative truck platooning

Author

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  • Abdolmaleki, Mojtaba
  • Shahabi, Mehrdad
  • Yin, Yafeng
  • Masoud, Neda

Abstract

A cooperative truck platoon is a set of virtually linked trucks driving with a small intra-vehicle headway enabled by connected and automated vehicle technologies. One of the primary benefits of truck platooning is energy savings due to the reduction of aerodynamic drag on the platooned vehicles. The focus of this paper is on scheduling travel itineraries of a given set of trucks to facilitate the formation of platoons to maximize energy savings. By constructing a time-expanded network, we formulate the problem as a minimum concave-cost network flow problem, and devise a few solution methods to find the optimal or high-quality solutions. The solution methods include an outer approximation algorithm for solving a mixed-integer convex minimization reformulation of the problem, a dynamic-programming-based heuristic scalable to large-scale instances, and a fast approximation algorithm with guaranteed performance for a restrictive version of the problem. All the proposed algorithms are examined and benchmarked on medium to large networks under various test scenarios. The numerical results demonstrate the efficiency of the proposed methods and their applicability in real-world settings.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:transb:v:153:y:2021:i:c:p:91-110
    DOI: 10.1016/j.trb.2021.08.016
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    References listed on IDEAS

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    1. Masoud, Neda & Jayakrishnan, R., 2017. "A decomposition algorithm to solve the multi-hop Peer-to-Peer ride-matching problem," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 1-29.
    2. 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.
    3. Browand, Fred & McArthur, John & Radovich, Charles, 2004. "Fuel Saving Achieved in the Field Test of Two Tandem Trucks," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt29v570mm, Institute of Transportation Studies, UC Berkeley.
    4. Zabat, Michael & Stabile, Nick & Farascaroli, Stefano & Browand, Frederick, 1995. "The Aerodynamic Performance Of Platoons: A Final Report," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt8ph187fw, Institute of Transportation Studies, UC Berkeley.
    5. Duret, Aurelien & Wang, Meng & Ladino, Andres, 2020. "A hierarchical approach for splitting truck platoons near network discontinuities," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 285-302.
    6. 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.
    7. Walter Murray & Kien-Ming Ng, 2010. "An algorithm for nonlinear optimization problems with binary variables," Computational Optimization and Applications, Springer, vol. 47(2), pages 257-288, October.
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    Cited by:

    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. 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).
    3. Yifeng Han & Tomoya Kawasaki & Shinya Hanaoka, 2022. "The Benefits of Truck Platooning with an Increasing Market Penetration: A Case Study in Japan," Sustainability, MDPI, vol. 14(15), pages 1-15, July.
    4. Boshuai Zhao & Roel Leus, 2022. "An improved decomposition-based heuristic for truck platooning," Papers 2210.05562, arXiv.org, revised Feb 2023.

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