IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v164y2022ics1366554522001958.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554522001958
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tre.2022.102806?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. 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, June.
    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.
    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. 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.
    2. Tengilimoglu, Oguz & Carsten, Oliver & Wadud, Zia, 2023. "Implications of automated vehicles for physical road environment: A comprehensive review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 169(C).
    3. Badia, Hugo & Jenelius, Erik, 2021. "Design and operation of feeder systems in the era of automated and electric buses," Transportation Research Part A: Policy and Practice, Elsevier, vol. 152(C), pages 146-172.
    4. Wadud, Zia & Mattioli, Giulio, 2021. "Fully automated vehicles: A cost-based analysis of the share of ownership and mobility services, and its socio-economic determinants," Transportation Research Part A: Policy and Practice, Elsevier, vol. 151(C), pages 228-244.
    5. Schweitzer, Nicola & Hofmann, Rupert & Meinheit, Andreas, 2019. "Strategic customer foresight: From research to strategic decision-making using the example of highly automated vehicles," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 49-65.
    6. Marletto, Gerardo, 2019. "Who will drive the transition to self-driving? A socio-technical analysis of the future impact of automated vehicles," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 221-234.
    7. Luo, Qi & Saigal, Romesh & Chen, Zhibin & Yin, Yafeng, 2019. "Accelerating the adoption of automated vehicles by subsidies: A dynamic games approach," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 226-243.
    8. Taiebat, Morteza & Stolper, Samuel & Xu, Ming, 2019. "Forecasting the Impact of Connected and Automated Vehicles on Energy Use: A Microeconomic Study of Induced Travel and Energy Rebound," Applied Energy, Elsevier, vol. 247(C), pages 297-308.
    9. Herbert Kopfer & Benedikt Vornhusen, 2019. "Energy vehicle routing problem for differently sized and powered vehicles," Journal of Business Economics, Springer, vol. 89(7), pages 793-821, September.
    10. 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.
    11. Abe, Ryosuke, 2019. "Introducing autonomous buses and taxis: Quantifying the potential benefits in Japanese transportation systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 94-113.
    12. Engholm, Albin & Kristoffersson, Ida & Pernestal, Anna, 2021. "Impacts of large-scale driverless truck adoption on the freight transport system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 227-254.
    13. Kolarova, Viktoriya & Steck, Felix & Bahamonde-Birke, Francisco J., 2019. "Assessing the effect of autonomous driving on value of travel time savings: A comparison between current and future preferences," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 155-169.
    14. Babagolzadeh, Mahla & Zhang, Yahua & Abbasi, Babak & Shrestha, Anup & Zhang, Anming, 2022. "Promoting Australian regional airports with subsidy schemes: Optimised downstream logistics using vehicle routing problem," Transport Policy, Elsevier, vol. 128(C), pages 38-51.
    15. Jinil Han & Chungmok Lee & Sungsoo Park, 2014. "A Robust Scenario Approach for the Vehicle Routing Problem with Uncertain Travel Times," Transportation Science, INFORMS, vol. 48(3), pages 373-390, August.
    16. Li, Dun & Huang, Youlin & Qian, Lixian, 2022. "Potential adoption of robotaxi service: The roles of perceived benefits to multiple stakeholders and environmental awareness," Transport Policy, Elsevier, vol. 126(C), pages 120-135.
    17. Ji, Chenlu & Mandania, Rupal & Liu, Jiyin & Liret, Anne, 2022. "Scheduling on-site service deliveries to minimise the risk of missing appointment times," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    18. Emberger, Guenter & Pfaffenbichler, Paul, 2020. "A quantitative analysis of potential impacts of automated vehicles in Austria using a dynamic integrated land use and transport interaction model," Transport Policy, Elsevier, vol. 98(C), pages 57-67.
    19. Jin Li & Feng Wang & Yu He, 2020. "Electric Vehicle Routing Problem with Battery Swapping Considering Energy Consumption and Carbon Emissions," Sustainability, MDPI, vol. 12(24), pages 1-20, December.
    20. Hatzenbühler, Jonas & Jenelius, Erik & Gidófalvi, Gyözö & Cats, Oded, 2023. "Modular vehicle routing for combined passenger and freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(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:164:y:2022:i:c:s1366554522001958. 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.