Proactive Integrated Detection of Eye Blinking & Yawning to identify Sleepy Driver and Alert based Auto-Braking System for Speed Control

Abstract

Automotive vehicles are increasingly being equipped with accident avoidance and warning systems for avoiding the external collision with an object, such as a vehicle or a human. Upon detecting a main factor, the system will start an action to avoid the collision and/or provide a warning to the vehicle operator. In this paper a complete accident avoidance system is proposed by determining the driver’s behavior. The main cause of vehicle accident is related to a main human factor, which is drowsiness. The aim of the proposed system is to help in analyzing the factors associated with driver’s behavior for the development of accident avoidance systems. The main causes of the vehicle accidents, coined in the tracking of the driver fatigue with the help of our system, will help the driver to avoid risky situations. In this project we are implementing two image processing tool to get the facial geometry based eye region detection for eye blinking calculation, combined tracking of mouth for yawning detection. Inside an ego vehicle, frequencies of eye blinking and eye closure and yawning frequencies are used as the indication of sleepy driver and warning sign is then generated for recommendation; Outside an ego vehicle, Ultrasonic sensor is used to measure distance in front of cars and auto-braking system is applied during unsuccessful drowsiness alert and also during brake failure situations.