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Impacts of electric and driverless heavy-duty trucks on the future decarbonized freight transport system: Analyzing techno-economic uncertainty using exploratory modeling and analysis

Author

Listed:
  • Engholm, Albin
  • Frölander, Simon
  • Johansson, Magnus
  • Kristofersson, Filip
  • Kristoffersson, Ida

Abstract

Predicting the impacts of a transition to a decarbonized freight transport system is challenging due to the inherent uncertainty surrounding the development and deployment of electric and automated truck technologies. This paper presents an exploratory analysis of techno-economic uncertainties for the deployment of electric trucks and automated driving technology and their impacts on the Swedish freight transport system by 2045. A modified version of the Swedish national freight model, Samgods, extended to represent manual electric trucks (METs) and automated driverless electric trucks (AETs), is used to analyze over 300 scenarios. In these scenarios, assumptions about the development and performance of METs and AETs are varied relative to the Swedish reference forecast for freight transport. System-level impacts including mode splits, logistics costs, and energy demand are analyzed. Higher levels of electric truck technology maturity correlate with reduced transport costs, increased road freight demand, and decreased reliance on biofuels. AETs further amplify these effects although with significant variation by operating model and technology maturity. Even without full SAE Level 5 automation, AETs operating exclusively on highways could, in some scenarios, perform over 75 % of domestic road transport tonne-kilometers, provided their unit economics are favorable. In addition to contributing by exploring a plausible outcome space of electrification and automated driving technology, this paper demonstrates a tractable approach for exploring system-level impacts of MET and AET deployment on logistics, mode shifts, and energy consumption with national-level freight models under uncertainty.

Suggested Citation

  • Engholm, Albin & Frölander, Simon & Johansson, Magnus & Kristofersson, Filip & Kristoffersson, Ida, 2025. "Impacts of electric and driverless heavy-duty trucks on the future decarbonized freight transport system: Analyzing techno-economic uncertainty using exploratory modeling and analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 199(C).
  • Handle: RePEc:eee:transa:v:199:y:2025:i:c:s0965856425002046
    DOI: 10.1016/j.tra.2025.104576
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    References listed on IDEAS

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    1. Yantao Huang & Kenneth A. Perrine & Kara M. Kockelman, 2024. "Impacts of automated trucks on U.S. freight movements: application and enhancement of the random-utility-based multiregional input-output model," Transportation Planning and Technology, Taylor & Francis Journals, vol. 47(8), pages 1423-1442, November.
    2. Verônica Ghisolfi & Lóránt Antal Tavasszy & Gonçalo Homem de Almeida Correia & Gisele de Lorena Diniz Chaves & Glaydston Mattos Ribeiro, 2022. "Freight Transport Decarbonization: A Systematic Literature Review of System Dynamics Models," Sustainability, MDPI, vol. 14(6), pages 1-30, March.
    3. 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.
    4. Johannes Karlsson & Anders Grauers, 2023. "Case Study of Cost-Effective Electrification of Long-Distance Line-Haul Trucks," Energies, MDPI, vol. 16(6), pages 1-22, March.
    5. Lange, Jan-Hendrik & Speth, Daniel & Plötz, Patrick, 2024. "Optimized demand-based charging networks for long-haul trucking in Europe," Working Papers "Sustainability and Innovation" S06/2024, Fraunhofer Institute for Systems and Innovation Research (ISI).
    6. Hong, Wanshi & Jenn, Alan & Wang, Bin, 2023. "Electrified autonomous freight benefit analysis on fleet, infrastructure and grid leveraging Grid-Electrified Mobility (GEM) model," Applied Energy, Elsevier, vol. 335(C).
    7. Tavasszy, Lóránt A., 2020. "Predicting the effects of logistics innovations on freight systems: Directions for research," Transport Policy, Elsevier, vol. 86(C), pages 1-6.
    8. Rich, J. & Kveiborg, O. & Hansen, C.O., 2011. "On structural inelasticity of modal substitution in freight transport," Journal of Transport Geography, Elsevier, vol. 19(1), pages 134-146.
    9. 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).
    10. 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.
    11. Patrick Plötz & Jakob Wachsmuth & Frances Sprei & Till Gnann & Daniel Speth & Felix Neuner & Steffen Link, 2023. "Greenhouse gas emission budgets and policies for zero-Carbon road transport in Europe," Climate Policy, Taylor & Francis Journals, vol. 23(3), pages 343-354, March.
    12. Jonathan Köhler & Fjalar de Haan & Georg Holtz & Klaus Kubeczko & Enayat Moallemi & George Papachristos & Emile Chappin, 2018. "Modelling Sustainability Transitions: An Assessment of Approaches and Challenges," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 21(1), pages 1-8.
    13. Johannes Karlsson & Anders Grauers, 2023. "Energy Distribution Diagram Used for Cost-Effective Battery Sizing of Electric Trucks," Energies, MDPI, vol. 16(2), pages 1-19, January.
    14. 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.
    15. Mehdi Jahangir Samet & Heikki Liimatainen & Oscar Patrick René van Vliet & Markus Pöllänen, 2021. "Road Freight Transport Electrification Potential by Using Battery Electric Trucks in Finland and Switzerland," Energies, MDPI, vol. 14(4), pages 1-22, February.
    16. 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.
    17. Plötz, Patrick & Wachsmuth, Jakob & Sprei, Frances & Gnann, Till & Speth, Daniel & Neuner, Felix & Link, Steffen, 2023. "Greenhouse gas emission budgets and policies for zero-carbon road transport in Europe," Working Papers "Sustainability and Innovation" S02/2023, Fraunhofer Institute for Systems and Innovation Research (ISI).
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