Pupillary Response and EMG Predict Upcoming Responses to Collision Avoidance Warning

Nowadays, an advanced driver assistance system (ADAS) has become popular in a new automobile. Even though cutting-edge technologies in ADAS provide high accuracy collision avoidance warnings, the distraction-related crashes caused by collision avoidance warnings are likely to become an emerging problem. Hence, it is necessary to understand how a driver responds to collision warning and how to reduce driver distraction caused by ADAS. Recent studies have found that physiological data, such as pupillary responses and electromyography (EMG), can forecast the human’s physical responses. Therefore, in this study, pupil and EMG signals were applied to predict drivers’ physical responses to collision warning. Logistic regression was applied to predict if drivers would like to give a physical response or not. The findings of the current study will contribute to improving the safety feature of collision warning systems and help to design the advanced driver assistance system with better device-user interaction.

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