We have proposed a driver assistance system with a dual control theoretic scheme, which tries to perform safety control of a vehicle as well as identification of a driver’s cognitive state simultaneously. To investigate the functionality and effectiveness on attaining safety and identifying driver state, we collected driver behavior data when the system was active. In this paper, driver state identification methods are proposed, and a trade-off relationship between detection accuracy of drowsy driving and time to detect drowsy driving are verified through a leave-one-out cross-validation technique.
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