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

Tomasz Neumann () and Radosław Łukasik
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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

Energies, 2025, vol. 18, issue 16, 1-22

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.

Keywords: transportation; traffic safety; self-driving vehicles; digital tachograph; professional driver working time (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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