Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota
This project is the extension of Northland Advanced Transportation System Research Laboratory (NATSRL) FY
2008 and FY2009 projects titled, “Real-time Nonintrusive Detection of Driver Drowsiness,” which aims to develop
a real-time, nonintrusive driver drowsiness detection system to reduce drowsiness-cause accidents. In our previous
research, nonintrusive sensors for drivers’ heart beat measurement were developed and implemented on the vehicle
steering wheel. Heart rate variability (HRV) was analyzed from the heart beat pulse signals for the detection of
driver drowsiness. Promising results were obtained. However, one of the major issues with the previous system is
using only one parameter, Low-Frequency (LF)/High-frequency (HF) ratio of HRV, to access the driver’s status,
which has relative high variability and has different changing patterns for different drivers. In this project, we used
multiple parameters for the drowsiness detection, including the LF/HF ratio, steering wheel motion variability and
Electroencephalography (EEG) parameters. Correlations between these parameters are analyzed.
Integrated Approach for Nonintrusive Detection of Driver Drowsiness.
Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota.
Retrieved from the University of Minnesota Digital Conservancy,
Content distributed via the University of Minnesota's Digital
Conservancy may be subject to additional license and use
restrictions applied by the depositor.