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Please use this identifier to cite or link to this item: http://hdl.handle.net/11299/138800

Title: Integrated Approach for Nonintrusive Detection of Driver Drowsiness
Authors: Yu, Xun
Keywords: Drowsiness
Heart rate
Electroencephalography
Steering wheels
Issue Date: Oct-2012
Publisher: Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota
Series/Report no.: CTS 12-32
Abstract: 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.
URI: http://purl.umn.edu/138800
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