Driver fatigue detection using machine learning methods

Abstract

With the development of technology and society, cars have become an indispensable part of people's daily life and business. As a result, the problem of traffic accidents has also become a considerable cause of casualties in society today. Driver fatigue detection is considered a promising technology to reduce traffic accidents. Cars can remind drivers or make corresponding actions when noticing that drivers are tired through the data transmitted by the detection system. Machine learning is the essential part of driver fatigue detection, which has the advantages of high performance and accuracy. Most driver fatigue detection Systems will use machine learning to get a better result. This article will analyze the Machine Learning currently used in driver fatigue detection, including Hidden Markov Model, Support Vector Machine, Gradient Boosting Decision Tree, Convolutional Neural Network, Deep Belief Networks, Recurrent neural network, and Radial Basic Function Network.