| Home | KSAE | E-Submission | Sitemap | Contact Us |  
International Journal of Automotive Technology > Volume 23(4); 2022 > Article
International Journal of Automotive Technology 2022;23(4): 917-926.
doi: https://doi.org/10.1007/s12239-022-0080-4
Deok Ho Nam 1#, Gyeong Pil Kim 1#, Keon Hee Baek 1, Da Som Lee 1, Ho Yong Lee 2, Myung Won Suh 3
1Graduate School of Mechanical Engineering, Sungkyunkwan University
2Urban Railroad Research Department, Korea Railroad Research Institute
3Department of Mechanical Engineering, Sungkyunkwan University
PDF Links Corresponding Author.  Ho Yong Lee  , Email. hylee@krri.re.kr
Use of an Automated Driving System is expected to improve traffic safety by protecting drivers from drowsy driving. Previous studies on the use of Automated Driving Systems mainly focused on detecting a driver’s level of drowsiness and protecting drivers from accidents by performing fallback maneuvers. However, maneuvers conducted in drowsy states are limited in their ability to achieve Minimal Risk Conditions because human drivers show a gradual degradation in their driving ability as they fall asleep and the probability of an accident increases greatly after a driver becomes drowsy. Thus, current Automated Driving Systems require algorithms to predict drowsiness and perform maneuvers before the driver becomes too drowsy. This paper suggests an algorithm that not only detects but also predicts driver drowsiness using 6 vehicle data points. Driver condition is classified into 4 states and Driver drowsiness can be predicted by detecting the severe fatigue state, which tends to occur one minute before the drowsy state. The vehicle driving data are collected using a simulator and features that can be used to distinguish between the 4 states are investigated through data analysis. Ultimat
Key Words: Driver drowsiness, Minimal risk condition, Light fatigue, Severe fatigue, Vehicle driving data, Machine learning algorithms
Editorial Office
21 Teheran-ro 52-gil, Gangnam-gu, Seoul 06212, Korea
TEL: +82-2-564-3971   FAX: +82-2-564-3973   E-mail: manage@ksae.org
About |  Browse Articles |  Current Issue |  For Authors and Reviewers
Copyright © The Korean Society of Automotive Engineers.                 Developed in M2PI
Close layer
prev next