An Algorithmic Approach to Driver Drowsiness Detection for Ensuring Safety in an Autonomous Car

Human-centric accidents are increasing gradually and one of the dominant causes of the accidents is driver drowsiness. Therefore, to lessen the accidents related to drowsiness, methods that are capable of observing facial expression to detect drowsiness have been proposed by researchers in recent decades to ensure safety. However, the state-of-the-art models only have the competency in determining the drowsiness and alarming the driver. Traditional approaches divide the detection method into two stages, such as detecting drowsiness from the driver's facial features and further apprising the driver. Hence, the existing models are inadequate to take any additional safety procedures to ensure more safety if the driver remains unable to operate the vehicle after giving an alarm. Analyzing these approaches and because of the increasing reliance on the vehicles, we have introduced an algorithmic approach in which the proposed system can locate a safe parking space after the determination of drowsiness and can also deliver a distress message to the authority informing about the situation while reaching at the safe parking space to assure safety from the incompetent, drowsy driver.