Work

Exploring ADAS driver training in driving academies: Perspectives from driving instructors

Year: 2025

Type: article

Abstract: As Advanced Driver Assistance Systems (ADAS) become integrated into vehicles, driver education is important to supporting the safe and effective use of these technologies. However, formal training programs for drivers remain underdeveloped. Notably, existing research on the safety implications of ADAS driver training often overlooks the perspectives of driving instructors, who are central to the safe and effective dissemination of these systems. To address this gap, this study explores the perspectives of professional driving instructors who have delivered structured ADAS training at driving academies across four European countries. Through semi-structured interviews with fourteen professional instructors, the study examines the training design, implementation challenges, instructional outcomes, demographic considerations, and institutional roles. The findings reveal that ADAS driver training improves driver confidence and encourages appropriate system use, particularly by reducing overreliance on automation. Instructors emphasised the importance of a phased training model, combining theoretical instruction, controlled-track practice, and real-world driving. They also highlighted the need for tailored approaches for older drivers and for introducing ADAS training after novice drivers have acquired basic driving skills. Instructors identified systemic barriers such as inconsistent ADAS functionality across vehicle brands and limited integration with dealership and fleet management practices. This study highlights the need for standardised ADAS training protocols and cross-sector collaboration among leasing companies, car dealerships, and regulatory bodies to ensure broad accessibility and effective learning. The findings contribute to developing scalable, inclusive, and safety-oriented frameworks for driver education in emerging vehicle technologies.

Source: Safety Science

DOI: 10.1016/j.ssci.2025.107042

Authors: Soyeon Kim, Simeon Calvert, Marjan Hagenzieker

Institution: Delft University of Technology

Language: English

Topic: Human-Automation Interaction and Safety

Subfield: Social Psychology

Field: Psychology

Domain: Social Sciences

SDG: Quality education

Open Access status: hybrid

Estimated APC paid: $4,360