Validity Analysis of Vehicle and Physiological Data for Detecting Driver Drowsiness, Distraction, and Workload

This study aims to validate vehicle and physiological readouts for the assessment of a driver's state. According to the Korea Transportation Safety Authority's report (2012), 22.5% of 1000 drivers have experienced a crash or near-crash caused by drowsy or distracted driving. In this paper, 2 simulated driving-environment experiments were designed. One experiment was performed to analyze various characteristics of drowsy drivers. Four subjects participated in 2 experimental sessions with 2 different sleep durations the day prior to the experiment (above 7 hours of sleep versus below 4 hours of sleep). Subjects were expected to drive on a highway road at 80 km/h. Another experiment was designed to analyze the characteristics of distracted or high workload drivers. Sixteen subjects participated in 1 experimental session requiring different levels of distraction or difficulty (e.g., driving while conducting a secondary task versus driving only). Subjects were expected to drive on a downtown road at 40 or 60 km/h depending on the level of difficulty. The present study indicated that vehicle and physiological data have the potential to assess drowsiness, distraction, and high workload driving. The vehicle and physiological data validated in this study will be incorporated into a driver's state-assessment algorithm in the future.