Fatigue driving detection of urban road at night based on multimodal information fusion

被引:0
|
作者
Wang W.X. [1 ]
Sun B.G. [1 ]
Xia R. [1 ]
机构
[1] College of Computer Engineering, Chongqing College of Humanities, Science & Technology, Hechuan, Chongqing
来源
Advances in Transportation Studies | 2023年 / 2卷 / Special issue期
关键词
fatigue driving at night; fatigue testing; multi parameter extraction; multi task learning; multimodal information fusion;
D O I
10.53136/979122180834615
中图分类号
学科分类号
摘要
Due to the poor accuracy, low efficiency and poor stability of fatigue driving detection of urban road at night, this paper proposes a fatigue driving detection of urban road at night based on multimodal information fusion. Firstly, the multi parameter extraction of fatigue driving state of driver's eyes, mouth and head is completed; Then, based on multimodal information fusion rules, the weighted average method is used to measure fatigue parameters and achieve classification of fatigue state levels. Finally, the fatigue detection model of the neural network is established, and the driver's fatigue detection is completed through SVM model classification. The experimental results show that this method can effectively realize accurate detection of fatigue driving of urban roads at night. © 2023, Aracne Editrice. All rights reserved.
引用
收藏
页码:171 / 188
页数:17
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