Comparative Analysis of Techniques for Driver Drowsiness Detection

There are serious consequences for road safety when drivers are sleepy or exhausted. If sleepy drivers are alerted in time, many tragedies can be avoided. There are a number of drowsiness detection technologies that can be used to keep tabs on a driver's alertness levels and sound an alarm if they start to drift off. Drowsiness can be inferred from facial expressions such as eye closure, head motions and yawing which contain the essential traits. Driver sleepiness detection takes into account both the drivers' physical state and the way their vehicles are being driven. This study provides a thorough evaluation of the current approaches for detecting driver fatigue, as well as a complete evaluation of popular classification strategies in this area. To begin, this study organizes the current methods into three broad classes. They rely on people's behavior, on their cars, and on their physiological data. Secondly, some other essential methods are discussed. Finally, a comparative analysis of existing methods has been done in a comprehensive approach.