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A systematic review for the fatigue driving behavior recognition method.

Authors :
Hou, Junjian
Xu, Yaxiong
He, Wenbin
Zhong, Yudong
Zhao, Dengfeng
Zhou, Fang
Zhao, Mingyuan
Dong, Shesen
Source :
Journal of Intelligent & Fuzzy Systems; 2024, Vol. 46 Issue 1, p1407-1427, 21p
Publication Year :
2024

Abstract

Fatigue driving is one of the primary causative factors of road accidents. It is of great significance to discern, identify and warn drivers in time for traffic safety and reduce traffic accidents. In this paper, a systematic review for the fatigue driving behavior recognition method is developed to analyze its research status and development trends. Firstly, the data information and its application scenarios related to fatigue driving is detailed. Three driving behavior recognition methods based on different types of signal data are summarized and analyzed, and this signal data can be divided into physiological signal characteristics, visual signal characteristics, vehicle sensor data characteristics and multi-data information fusion. By summarizing and comparing the recognition effect of existing fatigue driving recognition methods, combined with deep learning technology, the paper concludes the fatigue driving behavior recognition method based on single data source has some shortcomings such as low accuracy and easy to be affected by external factors, but the recognition method based on multi-feature information fusion can achieve a exhilarated recognition result. Finally, some prospects are given to analyze the development trend of fatigue driving behavior recognition in the future. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10641246
Volume :
46
Issue :
1
Database :
Complementary Index
Journal :
Journal of Intelligent & Fuzzy Systems
Publication Type :
Academic Journal
Accession number :
175159992
Full Text :
https://doi.org/10.3233/JIFS-235075