Preparing drivers for the future: Evaluating the effects of training on drivers’ performance in an autonomous vehicle landscape

The rapid development of Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicle (AV) technology has raised concerns about the ability of ordinary drivers to safely interact with these systems without formal training or practice sessions. This study investigates the impact of training on drivers' ability to interact with ADAS functions, aiming to enhance road safety and prepare drivers for future autonomous driving. To do so the study compared novice and experienced drivers' performance across various driving training sessions separated by different time intervals. Using a simulation-based driving scenario, a diverse group of participants with different ages, genders, driving experience, and ADAS usage frequencies was recruited. Participants were instructed to drive a virtual subject vehicle (SV) multiple times with different time intervals and various ADAS functions being activated and/or deactivated. Data on steering wheel input, acceleration, braking, event triggering time, response time, and vehicle lateral position were collected and analysed. Participants' performance, measured in terms of accuracy, reaction time in interacting with ADAS functions, and vehicle control when they are interacting with those functions, was assessed after each training session. Results revealed significant improvements in accuracy, reaction time, and vehicle control for both novice and experienced drivers' performance following training. The results highlight the importance of appropriate training for drivers to safely operate ADAS and autonomous functions, providing valuable insights for policymakers, vehicle manufacturers, and driver education institutions. Furthermore, the findings emphasise the need for further investigations on the effectiveness of various training modalities and the potential benefits of integrating real-time feedback systems or Artificial Intelligence (AI)-assisted coaching. This study has important ramifications for the future design and implementa