Detection of Driver Fatigue Caused by Sleep Deprivation
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Authors
Yang, Ji Hyun
Mao, Zhi-Hong
Tijerina, Louis
Pilutti, Tom
Coughlin, Joseph F.
Feron, Eric
Subjects
Bayesian networks (BNs)
camouflage
drowsy driving
sleep deprivation
stimulus-response tasks
tracking tasks
camouflage
drowsy driving
sleep deprivation
stimulus-response tasks
tracking tasks
Advisors
Date of Issue
2009-07
Date
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Abstract
This paper aims to provide reliable indications of
driver drowsiness based on the characteristics of driver–vehicle
interaction. A test bed was built under a simulated driving
environment, and a total of 12 subjects participated in two experiment
sessions requiring different levels of sleep (partial sleepdeprivation
versus no sleep-deprivation) before the experiment.
The performance of the subjects was analyzed in a series of
stimulus-response and routine driving tasks, which revealed
the performance differences of drivers under different sleepdeprivation
levels. The experiments further demonstrated that
sleep deprivation had greater effect on rule-based than on skillbased
cognitive functions: when drivers were sleep-deprived, their
performance of responding to unexpected disturbances degraded,
while they were robust enough to continue the routine driving
tasks such as lane tracking, vehicle following, and lane changing.
In addition, we presented both qualitative and quantitative guidelines
for designing drowsy-driver detection systems in a probabilistic
framework based on the paradigm of Bayesian networks.
Temporal aspects of drowsiness and individual differences of subjects
were addressed in the framework.
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Article
Description
The article of record as published may be located at http://dx.doi.org/10.1109/TSMCA.2009.2018634
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Citation
IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, Vol. 39, No. 4, July 2009.
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This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.