Open AccessOverview of approaches to driver fatigue recognition and existing technical solutions
Author(s) -
Ya.D. Saprykin,
V I Ryazantsev,
А. А. Смирнов
Publication year - 2020
Publication title -
izvestiâ mgtu "mami"
Language(s) - English
Resource type - Journals
eISSN - 2949-1428
pISSN - 2074-0530
DOI - 10.31992/2074-0530-2020-45-3-48-58
Subject(s) - computer science , state (computer science) , work (physics) , falling (accident) , engineering , psychology , mechanical engineering , algorithm , psychiatry
The article analyzes the existing methods for determining the driver's condition. Driving in a state of fatigue, according to various statistics, is the cause of a large number of road traffic accidents (RTA). The percentage of accidents in Russia associated with the driver falling asleep while driving in 2018 is about 20%, in the USA the number of accidents for the same reason reaches 100,000 per year. The aim of the work is to review existing approaches to recognizing driver fatigue and existing technical solutions in this area. The article discusses such approaches as fatigue recognition based on the physiological state of the driver, recognition based on the driver's behavior, namely his speech and visual signs while driving, fatigue determination based on the nature of the vehicle's movement on the road and based on the driver's actions on the controls, the approaches based on the subjective assessment of the driver's condition. The advantages and disadvantages of each of the approaches were analyzed. The paper also provides an overview of existing fatigue recognition systems from various manufacturers that are currently used on vehicles and are designed to warn the driver of impending fatigue. It was revealed that in modern conditions of road transport operation, the most optimal approaches to fatigue recognition are based on an assessment of the driver's impact on the steering wheel, visual signs of driver fatigue and the nature of the vehicle's movement on the road, therefore, it is proposed to further focus on these methods.