Multidimensional Analysis of Driver Uncertainty in Lane-Change Takeovers: Subjective, Performance, and Physiological Perspectives

In high-level autonomous driving, driver uncertainty during lane-changing takeovers presents a major challenge to human-machine coordination and traffic safety. This study explores driver physiological and behavioral responses under uncertainty, establishing a multidimensional evaluation framework. A driving simulator experiment is designed with controlled variables including time-to-collision (TTC), inter-vehicle gap, and relative speed. Physiological signals—ECG, EDA, and EMG—alongside driving behavior data are collected and time-aligned across takeover phases. Statistical analysis shows that EDA and EMG metrics significantly differ across uncertainty levels, while reaction time, lateral velocity, steering angle, and lane deviation also vary accordingly. Reaction time is negatively correlated with subjective uncertainty ratings. Moreover, uncertainty peaks are delayed with increasing relative speed but show no linear relationship with TTC or gap. These findings confirm the feasibility and effectiveness of integrating physiological and behavioral data for uncertainty assessment in autonomous takeover scenarios.