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Driver Cognitive Distraction Detection Using Eye Movements

  • Yulan Liang
  • John D. Lee
Part of the Signals and Commmunication Technologies book series (SCT)

Abstract

Driver distraction is an important safety problem [518]. The results of a study that tracked 100 vehicles for one year indicated that nearly 80% of crashes and 65% of near-crashes involved some form of driver inattention within three seconds of the events. The most common forms of inattention included secondary tasks, driving-related inattention, fatigue, and combinations of these [325]. In-vehicle information systems (IVIS), such as navigation systems and internet services, introduce various secondary tasks into the driving environment that can increase crash risk [5,516]. Thus, in future it would be very beneficial if IVIS could monitor driver distraction so that the system could adapt and mitigate the distraction. To not disturb driving, non-intrusive and real-time monitoring of distraction is essential.

Keywords

False Alarm Rate Secondary Task Smooth Pursuit Data Mining Method Visual Distraction 
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

  • Yulan Liang
    • 1
  • John D. Lee
    • 1
  1. 1.Department of Mechanical and Industrial EngineeringUniversity of IowaIowa CityUSA

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