Traffic injury prevention · 2026
What affects the quality of takeovers? A research on driver stress response and takeover performance in L3 autonomous driving from a multifactor coupling perspective.
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Ai Yuxin, Guo Fengxiang, Tang Yujie, Zhou Yiwen, Li Jingyang, Wan Huasen, Li Chunmei
Аннотация
OBJECTIVE: To investigate how acute stress response, takeover scenario urgency, non-driving-related tasks (NDRTs), and driver age jointly influence takeover performance during Level 3 automated driving.
METHODS: A driving simulator experiment was conducted with 50 drivers from three age groups (young, middle, older). Participants performed takeovers under emergency and nonemergency scenarios with three NDRT conditions (monitoring, music, video). Acute stress was quantified using a fuzzy logic model integrating heart rate, heart rate variability (SDNN), and skin conductance level. Takeover performance was comprehensively evaluated via a CRITIC-weighted composite score of reaction time, steering stability, mean speed, and maximum brake pedal depression.
RESULTS: Age was the dominant factor influencing both stress response and takeover performance. Younger drivers exhibited stronger physiological stress reactivity, whereas middle-aged drivers achieved the best takeover performance. Emergency scenarios yielded significantly better performance than nonemergency conditions. Although NDRTs affected individual driving-performance indicators, they did not significantly influence the composite takeover performance score. No significant direct association was found between stress level and overall takeover performance; however, higher stress levels were accompanied by greater performance variability.
CONCLUSIONS: Acute stress may affect takeover performance indirectly through increased performance variability rather than through direct mean-level effects. These findings underscore the need for age-adaptive takeover systems and multidimensional performance evaluation in conditionally automated driving.
METHODS: A driving simulator experiment was conducted with 50 drivers from three age groups (young, middle, older). Participants performed takeovers under emergency and nonemergency scenarios with three NDRT conditions (monitoring, music, video). Acute stress was quantified using a fuzzy logic model integrating heart rate, heart rate variability (SDNN), and skin conductance level. Takeover performance was comprehensively evaluated via a CRITIC-weighted composite score of reaction time, steering stability, mean speed, and maximum brake pedal depression.
RESULTS: Age was the dominant factor influencing both stress response and takeover performance. Younger drivers exhibited stronger physiological stress reactivity, whereas middle-aged drivers achieved the best takeover performance. Emergency scenarios yielded significantly better performance than nonemergency conditions. Although NDRTs affected individual driving-performance indicators, they did not significantly influence the composite takeover performance score. No significant direct association was found between stress level and overall takeover performance; however, higher stress levels were accompanied by greater performance variability.
CONCLUSIONS: Acute stress may affect takeover performance indirectly through increased performance variability rather than through direct mean-level effects. These findings underscore the need for age-adaptive takeover systems and multidimensional performance evaluation in conditionally automated driving.