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Integrating Autonomous Trucks into Human-Centric Operations: A Path to Safer and More Energy-Efficient Road Transport

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  • Tomasz Neumann

    (Faculty of Navigation, Gdynia Maritime University, 81-225 Gdynia, Poland)

  • Radosław Łukasik

    (Faculty of Navigation, Gdynia Maritime University, 81-225 Gdynia, Poland)

Abstract

The increasing integration of autonomous driving technologies into heavy-duty road transport requires a clear understanding of how these systems affect professional drivers’ working time, vehicle utilization, and regulatory compliance. This study develops a model-based comparative analysis to assess the cooperation between human drivers and autonomous trucks at SAE Levels 3 and 4. Using EU Regulation (EC) No 561/2006 as a legal framework, single-driver, double-driver, and ego vehicle scenarios were simulated to evaluate changes in working time classification and vehicle movement. The results indicate that Level 3 automation enables up to 13.25 h of daily vehicle movement while complying with working time regulations, compared with the 10-h limit for conventional operation. Level 4 automation further extends the effective movement time to 14.25 h in double-crew configurations, offering opportunities for increased efficiency without violating labor codes. The novelty of this work lies in the quantitative modeling of human–machine collaboration in professional transport under real regulatory constraints. These findings provide a foundation for regulatory updates, tachograph adaptation to AI-driven vehicles, and the design of hybrid driver roles. Future research will focus on validating these models in real-world transport operations and assessing the implications of Level 5 autonomy for logistics networks and labor markets.

Suggested Citation

  • Tomasz Neumann & Radosław Łukasik, 2025. "Integrating Autonomous Trucks into Human-Centric Operations: A Path to Safer and More Energy-Efficient Road Transport," Energies, MDPI, vol. 18(16), pages 1-22, August.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:16:p:4219-:d:1720359
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    References listed on IDEAS

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    1. Jurijus Zaranka & Robertas Pečeliūnas & Vidas Žuraulis, 2021. "A Road Safety-Based Selection Methodology for Professional Drivers: Behaviour and Accident Rate Analysis," IJERPH, MDPI, vol. 18(23), pages 1-18, November.
    2. Eunbin Kim & Youngrim Kim & Jieun Park, 2022. "The Necessity of Introducing Autonomous Trucks in Logistics 4.0," Sustainability, MDPI, vol. 14(7), pages 1-10, March.
    3. Hoseon Kim & Jieun Ko & Cheol Oh & Seoungbum Kim, 2024. "Evaluation of Autonomous Driving Safety by Operational Design Domains (ODD) in Mixed Traffic," Sustainability, MDPI, vol. 16(22), pages 1-18, November.
    4. Xinyi Ren & Elizabeth Pritchard & Caryn van Vreden & Sharon Newnam & Ross Iles & Ting Xia, 2023. "Factors Associated with Fatigued Driving among Australian Truck Drivers: A Cross-Sectional Study," IJERPH, MDPI, vol. 20(3), pages 1-15, February.
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