Abstract—We implemented a fatigue driver detection system using a combination of driver’s state and driving behavior indicators. For driver’s state, the system monitored the eyes’ blinking rate and the blinking duration. Fatigue drivers have these values higher than normal levels. We used a camera with machine vision techniques to locate and observe driver’s blinking behavior. Harr’s cascade classifier was used to first locate the eye’s area, and once found, a template matching was used to track the eye for faster processing. For driving behavior, we acquired the vehicle’s state from inertial measurement unit (IMU) and gas pedal sensors. The principle component analysis (PCA) was used to select the components that have high variance. The variance values were used to differentiate fatigue drivers, which are assumed to have higher driving activities, from normal drivers.

Index Terms—fatigue driving, blink detection, driving behavior

Cite: Wasan Tansakul and Poj Tangamchit, "Fatigue Driver Detection System Using a Combination of Blinking Rate and Driving Inactivity," Jounal of Automation and Control Engineering, Vol. 4, No. 1, pp.33-39, February, 2016. doi: 10.12720/joace.4.1.33-39