Modeling drowsy driving behaviors

Excessive sleepiness may result in an increased risk of a motor vehicle crash either because the motorist falls asleep while driving or because he/she experiences reduced attention to road events and driving tasks due to sleepiness/inattention. This study was designed to investigate noninvasive measurable patterns that predict driving-related sleepiness and inattention. Seventeen residents-in-training (residents) recruited from the Indiana University Hospital took five-session driving tests on a driving simulator. Driving, sleep diary, questionnaire, and electroencephalogram (EEG) information were recorded for subsequent data analysis. With statistical and computational intelligence tools, some basic driving behaviors associated with inattention and sleepiness were identified. Results suggest that a combination of standard deviation of lateral lane position and standard deviation of steering wheel angle is a possible measure of the relationships between driving behaviors and road risks. The derived patterns are also consistent with other non-invasive measurements of sleepiness such as Epworth Sleepiness Scale and Stanford Sleepiness Scale.