The impact of emotion on takeover performance in human-machine shared driving

This study aimed to explore the performance differences of different emotions on driver takeover performance in L3 automated driving systems. 48 driving-experienced college students were recruited. Based on the two-dimensional emotion model, four emotions of valence (positive/negative) × arousal (high/low) were selected for induction and verification. Driving behavior data was collected in a simulated driving environment. Driving tasks included 4 obstacle avoidance scenarios. Results show that valence approximately affects takeover time and significantly affects vehicle longitudinal control. Negative emotions led to longer takeover times and sad led to worse longitudinal vehicle control. Arousal had a greater impact on lateral performance. Under high-arousal emotions, drivers have more unstable steering wheel control. This study is of great significance for optimizing automated driving system design and improving driving safety and driver experience.