Driver identification and fatigue detection algorithm based on deep learning
In order to avoid traffic accidents caused by driver fatigue, smoking and talking on the phone, it is necessary to design an effective fatigue detection algorithm. Firstly, this paper studies the detection algorithms of driver fatigue at home and abroad, and analyzes the advantages and disadvantages...
Main Authors: | Yuhua Ma, Ye Tao, Yuandan Gong, Wenhua Cui, Bo Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
AIMS Press
2023-02-01
|
Series: | Mathematical Biosciences and Engineering |
Subjects: | |
Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2023355?viewType=HTML |
Similar Items
-
Test Methods and Trends of Driving Fatigue Risk Assessment
by: Qinhong FAN, et al.
Published: (2021-07-01) -
Review of Research on Fatigue Driving Detection Based on Driver Facial Features
by: YANG Yanyan, LI Leixiao, LIN Hao
Published: (2023-06-01) -
Scented Solutions: Examining the Efficacy of Scent Interventions in Mitigating Driving Fatigue
by: Xinyue Jiang, et al.
Published: (2024-04-01) -
Correlation between Driver Subjective Fatigue and Bus Lateral Position in a Driving Simulator
by: Faramarz Gharagozlou, et al.
Published: (2015-08-01) -
How to Counteract Driver Fatigue during Conditional Automated Driving—A Systematic Review
by: Alexandra Loew, et al.
Published: (2024-03-01)