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MOVES Human Factors and Training Systems Focus Group
Naval Postgraduate School
The MOVES Institute
700 Dyer Road
Monterey, CA 93943-5001

   

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Date: October 9, 2007
Guest Speaker: Dr. Ji Hyun Yang of MIT Dept. of Aeronautics and Astronautics
Topic: Analysis and Detection of Driver Fatigue Caused by Sleep Deprivation
Abstract:
Human errors in attention and vigilance are among the most common causes of transportation accidents. Thus, effective countermeasures are crucial for enhancing road safety. By pursuing a practical and reliable design of an Active Safety system which aims to predict and avoid road accidents, we identify the characteristics of drowsy driving and devise a systematic way to infer the state of driver alertness based on driver-vehicle data. Although sleep and fatigue are major causes of impaired driving, neither effective regulations nor acceptable countermeasures are available yet.
 
We first analyze driver-vehicle systems with discrete sleep-deprivation levels, and reveal differences in the performance characteristics of drivers. Inspired by the human sleep-wake cycle mechanism and attributes of driver-vehicle systems, we design and perform human-in-the-loop experiments in a test bed built with STISIM Drive, an interactive fixed-based driving simulator. In the simulated driving, participants were given various driving tasks and secondary tasks for both non and partially sleep-deprived conditions. This experiment demonstrates that sleep deprivation has a greater effect on rule-based tasks than on skill-based tasks; when drivers are sleep-deprived, their performance of responding to unexpected disturbances degrades while they are robust enough to continue such routine driving tasks as straight lane tracking, following a lead vehicle, lane changes, etc.
 
In the second part, we present both qualitative and quantitative guidelines for designing drowsy driver detection systems in a probabilistic framework based on the Bayesian network paradigm and experimental data. We consider two major causes of sleep, i.e., sleep debt and circadian rhythm, in the framework with various driver-vehicle parameters, and also address temporal aspects of drowsiness and individual differences of subjects. The thesis concludes that detection of drowsy driving based on driver-vehicle data is a feasible but difficult problem which has diverse issues to be addressed; the ultimate challenge lies in the human operator.
 
Date: May 22, 2007
Guest Speaker: Dr John Golding, Univ of Westminster, London
 
Date: April 24, 2007
Guest Speaker: Dr. Jim Blascovich, UCSB and Research Center for Virtual Environments and Behavior (ReCVEB)
Topic: Virtual Reality and the Clash Consciousness, ppt slides
Web: bio
 
Date: 17 April, 2007
Topic: Expert Panel--Conducting Experiments at NPS

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