IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v154y2021icp227-254.html
   My bibliography  Save this article

Impacts of large-scale driverless truck adoption on the freight transport system

Author

Listed:
  • Engholm, Albin
  • Kristoffersson, Ida
  • Pernestal, Anna

Abstract

This paper presents an analysis of the potential impacts of large-scale adoption of driverless trucks on transport patterns and system costs for a national freight transport system with Sweden as a case study. The analysis is performed by extending the application domain of the Swedish national freight transport model Samgods to analyze two types of driverless truck scenarios. The first scenario represents a full adoption of driverless trucks that can operate the complete road network and thereby substitute manually driven trucks. In this scenario, road transport tonne-kilometers on Swedish territory increase by 22%, vehicle kilometers traveled by trucks increase by 35% and annual total system costs decrease by 1.7 B€ compared to a baseline scenario without driverless trucks. In the second scenario, the current fleet of manually driven trucks is complemented by driverless trucks that can operate on major roads between logistics hubs, but not in complex traffic environments like urban areas due to a limited operational design domain. This may be an initial use-case for driverless trucks operating on public roads. In this scenario, road tonne-kilometers increase by 11%, truck vehicle kilometers traveled increase by 15%, and annual total system costs decrease by 1.2 B€ compared to the baseline. For both scenarios, the impacts of driverless trucks vary significantly between commodity types and transport distances which suggests heterogeneity of benefits of automated driving between different types of freight flows. A sensitivity analysis is performed in which the costs for driverless truck operations is varied, and for the second scenario, also which parts of the road network that driverless trucks can operate are varied. This analysis indicates that the magnitude of impacts is highly dependent on the cost level of driverless trucks and that the ability for DL-trucks to perform international, cross-border transport is crucial for achieving reductions in system costs. An overarching conclusion of the study is that driverless trucks may lead to a significant increase in road transport demand due to modal shifts from rail and sea as a result of the improved cost performance of road transport. This would further strengthen the need to decarbonize road transport to meet non-negotiable climate targets. Important topics for future research include assessing potential societal costs related to driverless trucks due to infrastructure investments and negative externalities such as increasing CO2 emissions and congestion.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:transa:v:154:y:2021:i:c:p:227-254
    DOI: 10.1016/j.tra.2021.10.014
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856421002627
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tra.2021.10.014?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. 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.
    2. Simpson, Jesse R. & Mishra, Sabyasachee & Talebian, Ahmadreza & Golias, Mihalis M., 2019. "An estimation of the future adoption rate of autonomous trucks by freight organizations," Research in Transportation Economics, Elsevier, vol. 76(C).
    3. Anna Pernestål & Albin Engholm & Marie Bemler & Gyözö Gidofalvi, 2020. "How Will Digitalization Change Road Freight Transport? Scenarios Tested in Sweden," Sustainability, MDPI, vol. 13(1), pages 1-18, December.
    4. Aggelos Soteropoulos & Martin Berger & Francesco Ciari, 2019. "Impacts of automated vehicles on travel behaviour and land use: an international review of modelling studies," Transport Reviews, Taylor & Francis Journals, vol. 39(1), pages 29-49, January.
    5. Yantao Huang & Kara M. Kockelman, 0. "What will autonomous trucking do to U.S. trade flows? Application of the random-utility-based multi-regional input–output model," Transportation, Springer, vol. 0, pages 1-28.
    6. Itf, 2017. "Managing the Transition to Driverless Road Freight Transport," International Transport Forum Policy Papers 32, OECD Publishing.
    7. 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.
    8. Monios, Jason & Bergqvist, Rickard, 2019. "The transport geography of electric and autonomous vehicles in road freight networks," Journal of Transport Geography, Elsevier, vol. 80(C).
    9. Melander, Lisa & Dubois, Anna & Hedvall, Klas & Lind, Frida, 2019. "Future goods transport in Sweden 2050: Using a Delphi-based scenario analysis," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 178-189.
    10. Yantao Huang & Kara M. Kockelman, 2020. "What will autonomous trucking do to U.S. trade flows? Application of the random-utility-based multi-regional input–output model," Transportation, Springer, vol. 47(5), pages 2529-2556, October.
    11. Fritschy, Carolin & Spinler, Stefan, 2019. "The impact of autonomous trucks on business models in the automotive and logistics industry–a Delphi-based scenario study," Technological Forecasting and Social Change, Elsevier, vol. 148(C).
    12. Kallio, A.M.I. & Salminen, O. & Sievänen, R., 2016. "Forests in the Finnish low carbon scenarios," Journal of Forest Economics, Elsevier, vol. 23(C), pages 45-62.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Catherine Taylor & Robert Waschik, 2022. "Evaluating the impact of automation in long-haul trucking using USAGE-Hwy," Centre of Policy Studies/IMPACT Centre Working Papers g-326, Victoria University, Centre of Policy Studies/IMPACT Centre.
    2. Yan, Xiaoyuan & Xu, Min & Xie, Chi, 2023. "Local container drayage problem with improved truck platooning operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 169(C).
    3. Hopkins, Debbie & Schwanen, Tim, 2023. "Sociotechnical expectations of vehicle automation in the UK trucking sector," Technological Forecasting and Social Change, Elsevier, vol. 196(C).

    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. Anna Pernestål & Albin Engholm & Marie Bemler & Gyözö Gidofalvi, 2020. "How Will Digitalization Change Road Freight Transport? Scenarios Tested in Sweden," Sustainability, MDPI, vol. 13(1), pages 1-18, December.
    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. Talebian, Ahmadreza & Mishra, Sabyasachee, 2022. "Unfolding the state of the adoption of connected autonomous trucks by the commercial fleet owner industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    4. Huang, Yantao & Kockelman, Kara M. & Quarles, Neil, 2020. "How will self-driving vehicles affect U.S. megaregion traffic? The case of the Texas Triangle," Research in Transportation Economics, Elsevier, vol. 84(C).
    5. 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.
    6. 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.
    7. 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.
    8. Martin Adler & Stefanie Peer & Tanja Sinozic, 2019. "Autonomous, Connected, Electric Shared vehicles (ACES) and public finance: an explorative analysis," Tinbergen Institute Discussion Papers 19-005/VIII, Tinbergen Institute.
    9. 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.
    10. 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.
    11. Nadafianshahamabadi, Razieh & Tayarani, Mohammad & Rowangould, Gregory, 2021. "A closer look at urban development under the emergence of autonomous vehicles: Traffic, land use and air quality impacts," Journal of Transport Geography, Elsevier, vol. 94(C).
    12. 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.
    13. 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.
    14. 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).
    15. Simpson, Jesse R. & Mishra, Sabyasachee & Talebian, Ahmadreza & Golias, Mihalis M., 2019. "An estimation of the future adoption rate of autonomous trucks by freight organizations," Research in Transportation Economics, Elsevier, vol. 76(C).
    16. 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.
    17. Almlöf, Erik & Nybacka, Mikael & Pernestål, Anna & Jenelius, Erik, 2022. "Will leisure trips be more affected than work trips by autonomous technology? Modelling self-driving public transport and cars in Stockholm, Sweden," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 1-19.
    18. 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.
    19. Sharma, Ishant & Mishra, Sabyasachee, 2022. "Quantifying the consumer’s dependence on different information sources on acceptance of autonomous vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 179-203.
    20. 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.

    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:transa:v:154:y:2021:i:c:p:227-254. 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/547/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.