Exploring Driver Diversity in Post-Takeover Stabilization Based on Demographic Data

Introduction: Conditionally automated vehicles promise significant advances in road safety, efficiency, and comfort. Objective: This study investigates the effects of driver demographic characteristics on stabilization times after taking over from fully automated driving. Methods: Using data sets from two driving simulator studies, we analyzed 704 takeover attempts by 58 drivers with diverse backgrounds. The study used linear mixed models to assess the influence of age, gender, driving experience, and previous simulator experience on stabilization times for speed, deceleration, heart rate, pupil diameter and off-road gaze duration ratio. Results: The analysis showed that age had a significant effect on driver speed, while gender, driving experience and simulator experience affected deceleration. Discussion: These results suggest that current models of post-takeover stabilization do not apply uniformly to all demographic groups and should better account for demographic differences. This highlights the need for personalized approaches in automated vehicle systems to improve safety and user experience.