Abstract
Vehicle accidents due to driver drowsiness is the major problem all over the world. It leads to millions of road accidents that result in fatal and non-fatal injuries and huge financial losses. To overcome vehicle accidents and provide safety to all commuters on the roads, a smart driver drowsiness detection system is required which can detect the drowsy state of the driver at an early stage. The behavioural measure provides the promising results to detect driver drowsiness at an early stage due to its non-intrusive nature. In this measure, various facial features, ML (Machine Learning) or DL (Deep Learning) based algorithms are analyzed various states of the driver to detect drowsiness. In this paper, a comparative study has been conducted that use ML and DL based algorithms to detect driver drowsiness. This study is aimed of finding effective AI (Artificial Intelligence) approach to detect driver drowsiness at an early stage.
Publisher
The Electrochemical Society
Cited by
5 articles.
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