Driver Alertness and Awareness Monitoring System

A lapse in driver alertness or awareness of surroundings is one of the leading causes of road accidents. Driving while distracted or drowsy triples the risk of loss of control and vehicular accident. With developments in computer vision and deep learning, it is now possible to monitor drivers using a smartphone camera and avoid this risk. We describe a method that uses smartphone cameras to monitor driver alertness and awareness. The system compares the driver’s face to the photo on his or her driver’s licence. It detects the drowsiness of the driver using a real-time video stream. It also classifies driver actions into 9 commonly occurring distraction categories or as safe driving. The front facing video stream of the driver’s phone is also used for monitoring road safety behaviour by estimating the distance to surrounding vehicles on the road and other risks such as pedestrians and signal violations. We have also developed a model that can classify the roads into one of the 4 categories - Good, Poor, Satisfactory and Very Poor using CNN. Lastly, the system alerts drivers to the possibility of increased accident risk based on various factors such as location, time of day, etc. Monitoring drivers and alerting them to possible loss of awareness significantly reduces road accident risk.