An Experimental Study on Drivers’ Eye Movement Behavior When Using an Automated Lane Change System

This study addresses the gap in understanding drivers’ eye movement behaviors during automated lane changes and explores the application of driver monitoring in personalizing highly automated driving systems. Through a driving simulator experiment, this study thoroughly investigated the relationship between participants’ eye movement behaviors and subjective perceptions. 37 participants each experienced 48 different automated lane changes in the experiment. Their subjective feedback on situational trust and system aggressiveness was collected through questionnaires, and eye movements related to gaze, blink, saccade, fixation, pupil diameter, and eyelid opening were monitored. The analysis identified 25 significant eye movement features. The experimental results show that lower situational trust during automated lane changes correlated with increased attention to side mirrors, decreased attention to the front vehicle in the original lane, reduced blink frequency and suppressed saccade amplitude which increased the duration of effective visual information acquisition, smaller pupil diameter and greater fluctuations indicating increased cognitive load. The extracted features proved effective in building predictive models for drivers’ subjective evaluations. This study provides practical recommendations for selecting eye movement features and implementing personalized automated lane-change systems through eye movement monitoring. Future research will focus on expanding the dataset, improving predictive model performance, and exploring the application of these models.