Citation

Ebrahim Shaik M. Transp. Res. Interdiscip. Persp. 2023; 21: e100864.

Copyright

(Copyright © 2023, Elsevier Publishing)

DOI

10.1016/j.trip.2023.100864

PMID

unavailable

Abstract

Driver drowsiness has emerged as one of the key factors in recent times' traffic accidents, which can result in fatalities, serious physical losses, large monetary losses, and significant property damage. Drowsiness in a driver can be brought on by long hours behind the wheel, drowsiness, fatigue, medicine, difficulty sleeping, and medical illnesses. A dependable technology that can identify driver drowsiness and warn the driver before an accident occurs is needed, according to statistics from several research. Many studies have been conducted in the previous to develop a reliable driver drowsiness detection and predictionsystem that uses a variety of parameters to gauge the driver's level of drowsiness. In this study, we analyzed the numerous measurements made by researchers, which were classified as physiological, vehicle-based, subjective, and behavioral measures. This article presenting a study of the fundamental problems with various sleepiness detection systems and how they are used to detect fatigue while driving. In order to warn a driver before a collision, this analysis will concentrate on what happens while driving and the advancement of technological methods that are intended to detect and, ideally, forecast driver drowsiness. For upcoming researchers to do baseline assessment in the particular field, this thorough review will provide a better understanding.

Language: en

Keywords

Detection; Driver; Drowsiness; Prediction; Review