Diagnostic tools for identifying sleepy drivers in the field.
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2013-05-06
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NTL Classification:NTL-SAFETY AND SECURITY-Highway Safety;NTL-SAFETY AND SECURITY-Human Factors;
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Abstract:The overarching goal of this project was to identify and evaluate cognitive and behavioral indices that are sensitive to sleep
deprivation and may help identify commercial motor vehicle drivers (CMV) who are at-risk for driving in a sleep deprived
state and may prove useful in field tests administered by officers. To that end, we evaluated indices of driver physiognomy
(e.g., yawning, droopy eyelids, etc.) and driver behavioral/cognitive state (e.g. distracted driving) and the sensitivity of these
indices to objective measures of sleep deprivation. The measures of sleep deprivation were sampled on repeated
occasions over a period of 3.5-months in each of 44 drivers diagnosed with Obstructive Sleep Apnea (OSA) and 22 controls
(matched for gender, age within 5 years, education within 2 years, and county of residence for rural vs. urban driving).
Comprehensive analyses showed that specific dimensions of driver physiognomy associated with sleepiness in previous
research and face-valid composite scores of sleepiness did not: 1) distinguish participants with OSA from matched controls;
2) distinguish participants before and after PAP treatment including those who were compliant with their treatment; 3)
predict levels of sleep deprivation acquired objectively from actigraphy watches, not even among those chronically sleep
deprived. Those findings are consistent with large individual differences in driver physiognomy. In other words, when
individuals were sleep deprived as confirmed by actigraphy watch output they did not show consistently reliable behavioral
markers of being sleep deprived. This finding held whether each driver was compared to him/herself with adequate and
inadequate sleep, and even among chronically sleep deprived drivers. The scientific evidence from this research study does
not support the use of driver physiognomy as a valid measure of sleep deprivation or as a basis to judge whether a CMV
driver is too fatigued to drive, as on the current Fatigued Driving Evaluation Checklist.. Fair and accurate determinations of
CMV driver sleepiness in the field will likely require further research on alternative strategies that make use of a
combination of information sources besides driver physiognomy, including work logs, actigraphy, in vehicle data recordings,
GPS data on vehicle use, and performance tests.
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