United States Department of Transportation
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An Evaluation of Emerging Driver Fatigue Detection Measures and Technologies [Final report]
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2009-06-01
[PDF-792.46 KB]
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TRIS Online Accession Number:01135601
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OCLC Number:429543690
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Edition:Final Report; January 2005 ¿ November 2006
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NTL Classification:NTL-INTELLIGENT TRANSPORTATION SYSTEMS-Driver Assistance Systems (Vehicles);NTL-INTELLIGENT TRANSPORTATION SYSTEMS-INTELLIGENT TRANSPORTATION SYSTEMS;NTL-SAFETY AND SECURITY-Vehicle Design;NTL-SAFETY AND SECURITY-SAFETY AND SECURITY;
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Abstract:Operator fatigue and sleep deprivation have been widely recognized as critical safety issues that cut across all modes in the transportation industry. FMCSA, the trucking industry, highway safety advocates, and transportation researchers have all identified driver fatigue as a high priority commercial vehicle safety issue. Fatigue affects mental alertness, decreasing an individual’s ability to operate a vehicle safely and increasing the risk of human error that could lead to fatalities and injuries. Sleepiness slows reaction time, decreases awareness, and impairs judgment. Fatigue and sleep deprivation impact all transportation operators (airline pilots, truck drivers, and railroad engineers, for example). Adding to the difficulty of understanding the fatigue problem and developing effective countermeasures to address operator fatigue is the fact that the incidence of fatigue is underestimated because it is so hard to quantify and measure. Obtaining reliable data on fatigue-related crashes is challenging because it is difficult to determine the degree to which fatigue plays a role in crashes. Fatigue, however, can be managed, and effectively managing fatigue will result in a significant reduction in related risk and improved safety. This study focuses on recent developments in mathematical models and vehicle-based operator alertness monitoring technologies. The major objective of this paper is to review and discuss many of the activities currently underway to develop unobtrusive, in-vehicle, real-time drowsy driver detection and fatigue-monitoring/alerting systems.
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