Research on fatigue detection method based on driving behavior

被引：0
|
作者：
Hu, Dun-Li [1 ,2 ]
Liu, Kang [3 ]
机构：
[1] School of Information Engineering, University of Science and Technology Beijing, Beijing 100083, China
[2] Beijing Key Laboratory of Urban Traffic Intelligent Control Technology, North China University of Technology, Beijing 100144, China
[3] School of Mechatranical Engineering, North China University of Technology, Beijing 100144, China
来源：
Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology | 2013年 / 33卷 / SUUPPL.1期
关键词：
D O I：
暂无
中图分类号：
TH13 [机械零件及传动装置];
学科分类号：
080203 ;
摘要：
Identification of driving state based on driving behavior is presented in this paper. The driving behavior data was collected from the driving simulation chamber under the experimental conditions. The operating characteristics in fatigue driving state were analyzed including the steering wheel and throttle amplitude changes. Then the duty ratio of no steering and the mean value of throttle amplitude were extracted as the discrimination index for fatigue state. The no steering time was optimized using variance analysis. Finally the Fisher linear discrimination algorithm was used to identify the driving state with high recognition accuracy.
引用
收藏
页码：160 / 163
相关论文
共 50 条
  • [1] Research on Driver Fatigue Driving Detection Method Based on Deep Learning
    Li, Xiaoping
    Bai, Chao
    [J]. 1600, Science Press (43): : 78 - 87
  • [2] Research on Driving Fatigue Detection Based on PERCLOS
    Zhang, Cuiqing
    Wei, Lizhen
    Zheng, Pei
    [J]. 4TH INTERNATIONAL CONFERENCE ON VEHICLE, MECHANICAL AND ELECTRICAL ENGINEERING (ICVMEE 2017), 2017, : 207 - 211
  • [3] Research on Fatigue Driving Detection Method Based on Lightweight Convolutional Neural Network
    Xu, Xiao-wei
    Liu, Chang-ran
    Yu, Xue-jing
    Xiong, Hao
    Qian, Feng
    [J]. 2020 IEEE 5TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION ENGINEERING (IEEE ICITE 2020), 2020, : 254 - 258
  • [4] Detection of fatigue driving behavior based on facial expression
    Ding, Ling
    Xiong, Xiaobing
    Bao, Zhenyu
    Hu, Luokai
    Chen, Yu
    Li, Bijun
    Cheng, Yong
    [J]. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2024, 46 (03) : 7143 - 7153
  • [5] Fatigue Driving Detection Method Based on Multiple Features
    Liu, JinFeng
    [J]. 2022 6TH INTERNATIONAL SYMPOSIUM ON COMPUTER SCIENCE AND INTELLIGENT CONTROL, ISCSIC, 2022, : 148 - 152
  • [6] A Method of the Driving Fatigue Detection System Based on PERCLOS
    Liu Jian-jiang
    Liu Ying
    Zheng Pei
    [J]. 2ND INTERNATIONAL SYMPOSIUM ON COMPUTER NETWORK AND MULTIMEDIA TECHNOLOGY (CNMT 2010), VOLS 1 AND 2, 2010, : 538 - 540
  • [7] Fatigue driving detection method based on IPPG technology
    Bi, Jiu-Ju
    Qin, Xun-Peng
    Hu, Dong-Jin
    Xu, Chen-Yang
    [J]. PROMET-TRAFFIC & TRANSPORTATION, 2023, 35 (04): : 540 - 551
  • [8] Research on the Behavior of Driver Fatigue Driving
    Du, Qiusheng
    [J]. 2013 3RD INTERNATIONAL CONFERENCE ON EDUCATION AND EDUCATION MANAGEMENT (EEM 2013), 2013, 26 : 434 - 437
  • [9] Research on ARM9-Based Fatigue Driving Detection
    Chen, Jingjing
    Cui, Yan
    [J]. ASIA-PACIFIC YOUTH CONFERENCE ON COMMUNICATION TECHNOLOGY 2010 (APYCCT 2010), 2010, : 139 - 142
  • [10] The research on fatigue driving detection algorithm
    Lin, Zhui
    Wang, Lide
    Zhou, Jieqiong
    Wang, Tao
    [J]. Journal of Software, 2013, 8 (09) : 2272 - 2279
12345