A Novel Approach to Detect Drowsy Driving Resulting From Sleep Loss and Sleep Pressure

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Sleep loss has become a modern-day epidemic, with a significant impact on daytime functioning, resulting in about 6000 fatal car crashes/year due to drowsy driving in the US and about 100/year in Canada. One potentially life-threatening outcome is increased driver fatigue, often resulting in serious motor vehicle accidents. The main objective of the proposed research is the development of a non-invasive, real-time and unobtrusive in-vehicle system to detect driver fatigue before a motor vehicle accident occurs. Our proposed system measures eye movements that precede drowsiness using infra-red (IR) eye tracking camera technology. These eye movements are classified online by our novel artificial intelligence algorithms to detect the antecedents of somnolence, to be used to alert the driver while driving. Here, using driving simulation technology, we aim to study the relationship between eye movement characteristics and the behavioural and electrophysiological warning signs of impending driver sleepiness. This will allow us to develop a method to detect sleepiness and alert drivers before impairment and lapses in judgement occur. We plan to develop a novel method to effectively detect drowsiness using only eye tracking data in: 1) varying sleep-pressure, and, 2) natural variations in drowsiness at different times of day or night. Ultimately, this will result in the commercialization of an "early warning system", as a countermeasure to drowsiness impairment in the transport-trucking industry, public transit and in individual passenger vehicles. We expect that this work will open up further avenues for research and applications about the fitness to drive due to various other causes, such as alcohol, drug use and distracted driving.