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Selection of vehicle size and extent of multi-drop deliveries for autonomous goods vehicles: An assessment of potential for change

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  • Bray, Garrett
  • Cebon, David

Abstract

This paper examines how vehicle size and multi-drop deliveries may change as a result of the removal of the driver cost for autonomous goods vehicles. Analysis is conducted by combining parameters derived from transport economics and vehicle engineering for a series of increasingly complex applications, ultimately incorporating a unique vehicle routing problem formulation for two multi-destination applications. It is concluded that while the removal of the driver cost produced the greatest savings, the use of smaller vehicles and fewer deliveries per journey could produce incremental savings, dependent on the application. The incremental savings and potential change in vehicle sizes and number of deliveries was greatest for applications: 1) where the human driver would otherwise constitute a greater proportion of overall cost (such as urban deliveries), 2) where there is greater dispersion of delivery locations relative to the origin depot, 3) where the value of the cargo time is higher. For a UK customer deliveries case study currently using 3.5 t vans, a shift to smaller 2.1 t vans performing 40–60% fewer stops per route could lead to an additional 7–16% of cost savings, or up to 75% savings when combined with the direct driver cost savings. By contrast, for a UK supermarket distribution case study using 44 t articulated trucks, the introduction of some 26 t rigids serving fewer stops per route indicated effectively negligible potential savings compared to the 22–32% of savings due to the removal of the driver. Conclusions are conditional on treating a number of aspects of the logistics system as fixed in order to isolate factors of interest. Realistically, such aspects may be subject to change in future scenarios under the combined impact of autonomous freight vehicles and other trends.

Suggested Citation

  • Bray, Garrett & Cebon, David, 2022. "Selection of vehicle size and extent of multi-drop deliveries for autonomous goods vehicles: An assessment of potential for change," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
  • Handle: RePEc:eee:transe:v:164:y:2022:i:c:s1366554522001958
    DOI: 10.1016/j.tre.2022.102806
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    1. G. B. Dantzig & J. H. Ramser, 1959. "The Truck Dispatching Problem," Management Science, INFORMS, vol. 6(1), pages 80-91, October.
    2. Bektas, Tolga & Laporte, Gilbert, 2011. "The Pollution-Routing Problem," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1232-1250, September.
    3. Vidal, Thibaut & Laporte, Gilbert & Matl, Piotr, 2020. "A concise guide to existing and emerging vehicle routing problem variants," European Journal of Operational Research, Elsevier, vol. 286(2), pages 401-416.
    4. Fagnant, Daniel J. & Kockelman, Kara, 2015. "Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 167-181.
    5. de Jong, Gerard & Ben-Akiva, Moshe, 2007. "A micro-simulation model of shipment size and transport chain choice," Transportation Research Part B: Methodological, Elsevier, vol. 41(9), pages 950-965, November.
    6. Wadud, Zia & MacKenzie, Don & Leiby, Paul, 2016. "Help or hindrance? The travel, energy and carbon impacts of highly automated vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 86(C), pages 1-18.
    7. Anil K. Madhusudhanan & Xiaoxiang Na & David Cebon, 2021. "A Computationally Efficient Framework for Modelling Energy Consumption of ICE and Electric Vehicles," Energies, MDPI, vol. 14(7), pages 1-15, April.
    8. Bray, Garrett & Cebon, David, 2022. "Operational speed strategy opportunities for autonomous trucking on highways," Transportation Research Part A: Policy and Practice, Elsevier, vol. 158(C), pages 75-94.
    9. Koç, Çağrı & Bektaş, Tolga & Jabali, Ola & Laporte, Gilbert, 2016. "Thirty years of heterogeneous vehicle routing," European Journal of Operational Research, Elsevier, vol. 249(1), pages 1-21.
    10. Abate, Megersa & de Jong, Gerard, 2014. "The optimal shipment size and truck size choice – The allocation of trucks across hauls," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 262-277.
    11. ., 2021. "Liberty, autonomy and needs," Chapters, in: Liberal Solidarity, chapter 4, pages 64-83, Edward Elgar Publishing.
    12. Carlos F. Daganzo, 2005. "Logistics Systems Analysis," Springer Books, Springer, edition 0, number 978-3-540-27516-9, December.
    13. Wadud, Zia, 2017. "Fully automated vehicles: A cost of ownership analysis to inform early adoption," Transportation Research Part A: Policy and Practice, Elsevier, vol. 101(C), pages 163-176.
    14. Donald Erlenkotter, 1990. "Ford Whitman Harris and the Economic Order Quantity Model," Operations Research, INFORMS, vol. 38(6), pages 937-946, December.
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