Human Performance and Behavior

John Bloomfield and Kathleen Harder, College of Architecture and Landscape Architecture Fatigue Detection: Can FatigueDetection Devices Predict the Driving Performance of Sleep-Deprived Drivers? Status: In progress This project is seeking to determine the relationship between sleep deprivation and driving performance and to determine whether impairments in driving performance caused by sleep deprivation can be predicted by fatiguedetection devices. If such impairments can be predicted, the researchers also hope to provide law enforcement with reliable benchmark data documenting the correlation between the devices and driving performance impairment. To carry out these objectives, driving performance data and various measures of impairment will be collected from a minimum of 20 subjects over a 20hour period, during which time the subjects will be kept awake. Driving performance data will be collected while each subject drives in a driving simulator, and impairment will be assessed with various measurement instruments including EyeCheck, the psychomotor vigilance test (PVT), and the digit symbol substitution test (DSST). If, when the resultant data are analyzed, reliable relationships between driving performance impairment and fatigue detection devices are found, they will be formulated in a way that aids their use by law enforcement officers. To date, the simulator scenario development is nearing completion. The researchers are negotiating with the Minnesota Trucking Association in order to obtain participation of truck drivers in the study. The Human Subjects Approval process is almost complete, and the researchers are working with the University’s General Clinical Research Center so that when the driving simulation portion of the study is complete, the subjects will be escorted to the GCRC, where they will be monitored until they are able to leave. Project URL: www.its.umn.edu /research/projects/2002031.html