Evolution and Recent Trends in Detecting Driver Drowsiness

Road accidents are the leading causes of mortality in the contemporary period globally. Drowsiness while driving is one of the primary causes of collisions that result in critical injuries, premature death, and considerable financial losses. There are several sleepiness detection techniques that track drivers' drowsiness levels while they are on the road and alert them if they are not paying attention. The purpose of the research is to understand the various methodologies being used to identify driver inattention at early stages and contribute to the prevention of accidents. It also explores the most recent techniques and technologies being used to combat driver drowsiness. Various features of a human being such as the head, mouth, and eyes to detect the early stages of drowsiness are used because they are less intrusive and more accurate. Further, the study depicts how these technologies are being evolved to utilize basic techniques such as vehicles or subjective or physiological measures to bring out a more robust and confirmed state of early drowsiness. The study frameworks are also explained in diagrammatic and tabular versions for easier comprehension. In the methodology, survey-based study findings are derived from the technique, which can help new researchers discover potential future work on the subject. Finally, the main contribution of the article is to investigate, identify, and choose the most effective measurement combinations to detect driver fatigue. In addition, it also compares various techniques from traditional to hybrid, their performances, and their limitations.