Driver Drowsiness Detection and Alert System Development Using Object Detection

Abstract

Fatigue driving is an invisible killer in car accidents and one of the main causes of traffic accidents. In order to reduce traffic accidents caused by driving fatigue, this research has developed a safety assist device to prevent such traffic accidents. In this research, a non-contact driver drowsiness detection and alert system is established in the vehicle cabin. The real-time facial image of the driver is obtained through the camera installed in front of the driver, and then the image is input to the NVIDIA Jetson TX2 embedded module. YOLO (You Only Look Once) object detection algorithm is used to detect the opening and closing of the driver's eyes, and by processing the eye area, to determine whether the driver is currently awake or fatigued while driving. The driver drowsiness detection and alert system established in this research can be applied to the vehicle interior environment to monitor the driving status. When the driver is fatigued, the system will simultaneously emit sound and light signals to promptly warn such dangerous driving behaviors. It can prevent the driver from continuing to drive when fatigued, and ensure driving safety.