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This paper proposes a novel approach for the real-time detection of sleep onset in fatigued drivers. Sleep onset is the most critical consequence of fatigued driving, as shown by statistics of fatigue-related crashes. Therefore, unlike previous related work, we separate the issue of sleep onset from the global analysis of the physiological state of fatigue. This allows us for formulating our approach as an event-detection problem. Real-time performance is achieved by focusing on a single visual cue (i.e. eye-state), and by a custom-designed template-matching algorithm for on-line eye-state detection.