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Alertometer: Detecting and Mitigating Driver Drowsiness and Fatigue Using an Integrated Human Factors and Computer Vision Approach

  • Riad I. Hammoud
  • Harry Zhang
Part of the Signals and Commmunication Technologies book series (SCT)

Abstract

A significant number of highway crashes are attributable to driver drowsiness and fatigue. Drowsiness-related crashes can often cause more serious occupant injuries than crashes that are not related to driver drowsiness [291]. In order to better understand and curtail this problem, human factors researchers and engineers have studied the problem of driver drowsiness and fatigue in a variety of driving environments (for example, driving simulators). They have determined the behavioral characteristics associated with driver drowsiness and investigated the effectiveness of different mitigation strategies.

Keywords

Driver Assistance System Hough Transformation Eyelid Closure Lane Departure Psychomotor Vigilance Task 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Riad I. Hammoud
    • 1
  • Harry Zhang
    • 2
  1. 1.World Headquarters of Electronics and Safety DivisionDelphi CorporationKokomoUSA
  2. 2.MotorolaTempeUSA

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