• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
  • Scopus
  • Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
  • Chinese S&T Journal Citation Reports
  • Chinese Science Citation Database
Volume 54 Issue 1
Feb.  2019
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Article Contents
XU Chuan, GUO Qiming, WANG Xuesong. Driver Behavior Response to Drowsiness Alarming at Different Levels[J]. Journal of Southwest Jiaotong University, 2019, 54(1): 189-195. doi: 10.3969/j.issn.0258-2724.20180254
Citation: XU Chuan, GUO Qiming, WANG Xuesong. Driver Behavior Response to Drowsiness Alarming at Different Levels[J]. Journal of Southwest Jiaotong University, 2019, 54(1): 189-195. doi: 10.3969/j.issn.0258-2724.20180254

Driver Behavior Response to Drowsiness Alarming at Different Levels

doi: 10.3969/j.issn.0258-2724.20180254
  • Received Date: 04 Apr 2018
  • Rev Recd Date: 02 Jul 2018
  • Available Online: 08 Jul 2018
  • Publish Date: 01 Feb 2019
  • To identify the timing of drowsiness driving warning is the key issue and a bottleneck of onboard drowsiness driving warning technology. Finding a rationale for warning timing using driver’s driving behavior response feature is an innovation. Therefore, after conducting a driving simulator experiment under the influence of drowsiness alarming, eye movement index, the percentage of eyelid closure (PERCLOS), and vehicle lateral position indexes (standard deviation of lateral position, average of lateral position, area of line exceeding) were recorded. Then, the differences in driving behavior between the pre-warning and post-warning in 15 seconds for each warning were compared using the paired Wilcoxon signed-rank test. The results demonstrated that under the drowsiness classification criterion, after the normal level of drowsiness warning, the mean of the standard deviation of lateral position and the mean of the area of line exceeding significantly dropped down by 0.129 1 and 8.574 4 respectively; after the serious level of drowsiness warning, although the mean of PERCLOS decreased by 0.044 9, the standard deviation of the lateral position and area of line exceeding did not significantly change and that the driver should stop and rest immediately.

     

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  • 国务院滨保高速天津" 10•7”特别重大交通事故调查组. 滨保高速天津" 10•7”特别重大交通事故调查报告[R]. 北京:中华人民共和国国务院, 2012
    国务院包茂高速陕西延安" 8•26”特别重大道路交通事故调查组. 包茂高速延安" 8•26”特大道路交通事故调查报告[R]. 北京: 中华人民共和国国务院, 2013
    国务院办公厅. 国务院关于加强道路交通安全工作的意见 [EB/OL].(2012-07-27) [2017-02-05]. http://www.gov.cn/zwgk/2012-07/27/content_2193042.htm
    中华人民共和国工业和信息化部. 关于进一步提高大中型客货车安全技术性能加强车辆《公告》管理和注册登记管理工作的通知[EB/OL].(2011-12-31)[2017-02-05]. http://www.miit.gov.cn/n1146295/n1652858/n1652930/n3757018/c3757341/content.html
    中华人民共和国交通运输部. 关于加强道路运输车辆动态监管工作的通知[EB/OL].(2011-03-19)[2017-02-05]. http://www.chinasafety.gov.cn/Contents/Channel_5330/2011/0413/128291/asset000010003301211_0_1302663969013.html
    G7智慧物联网公司. 中国物流大数据报告[EB/OL].(2017-01-13)[2017-02-05]. http://www.zqcn.com.cn/hongguan/201701/13/c491618.html
    WIERWILLE W, WREGGIT S, KIRN L, et al. Research on vehicle-based driver status/performance monitoring; development, validation, and refinement of algorithms for detection of driver drowsiness[R]. Washington D. C.: US National Hightway Traffic Safety Adiministration, 1994
    HORREY J, NOY I, FOLKARD S, et al. Research needs and opportunities for reducing the adverse safety consequences of fatigue[J]. Accident Analysis & Prevention, 2011, 43(2): 591-594
    王福旺,王宏. 长途客车驾驶员疲劳状态脑电特征分析[J]. 仪器仪表学报,2013,34(5): 1146-1152 doi: 10.3969/j.issn.0254-3087.2013.05.027

    WANG Fuwang, WANG Hong. EEG characteristic analysis of coach bus drivers in fatigue state[J]. Chinese Journal of Science Instrument, 2013, 34(5): 1146-1152 doi: 10.3969/j.issn.0254-3087.2013.05.027
    程如中,赵勇,戴勇,等. 基于Adaboost方法的车载嵌入式疲劳驾驶预警系统[J]. 北京大学学报(自然科学版),2012,48(5): 719-726

    CHENG Ruzhong, ZHAO Yong, DAI Yong, et al. An on-board embedded driver fatigue warning system based on Adaboost method[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 2012, 48(5): 719-726
    张希波,成波,冯睿嘉. 基于方向盘操作的驾驶人疲劳状态实时检测方法[J]. 清华大学学报(自然科学版),2010,50(7): 1072-1076

    ZHANG Xibo, CHENG Bo, FENG Ruijia. Real-time detection of driver drowsiness based on steering performance[J]. Journal of Tsinghua University (Science and Technology), 2010, 50(7): 1072-1076
    谭小强. 基于DSP技术的疲劳驾驶预警系统中车道偏离识别方法的研究[D]. 西安: 长安大学, 2010
    胥川,王雪松,陈小鸿. 无侵入测量指标的驾驶疲劳检测性能评估[J]. 西南交通大学学报,2014,49(4): 720-726 doi: 10.3969/j.issn.0258-2724.2014.04.025

    XU Chuan, WANG Xuesong, CHEN Xiaohong. Evaluating performance of non-intrusive indicators on drowsy driving detection[J]. Journal of Southwest Jiaotong University, 2014, 49(4): 720-726 doi: 10.3969/j.issn.0258-2724.2014.04.025
    叶柠,孙宇舸. 基于EEG小波包子带能量比的疲劳驾驶检测方法[J]. 东北大学学报(自然科学版),2012,33(8): 1088-1092

    YE Ning, SUN Yuge. A fatigue driving detection method based on wavelet packet sub-band energy ratio of EEG[J]. Journal of Northeastern University (Natural Science), 2012, 33(8): 1088-1092
    赵晓华,许士丽,茉建,等. 基于ROC曲线的驾驶疲劳脑电样本熵判定阈值研究[J]. 西南交通大学学报,2013,48(1): 178-183 doi: 10.3969/j.issn.0258-2724.2013.01.028

    ZHAO Xiaohua, XU Shili, RONG Jian, et al. Discriminating threshold of driving fatigue based on the electroencephalography sample entropy by receiver operating characteristic curve analysis[J]. Journal of Southwest Jiaotong University, 2013, 48(1): 178-183 doi: 10.3969/j.issn.0258-2724.2013.01.028
    王连震,裴玉龙. 基于贝叶斯网络的驾驶疲劳程度识别模型[J]. 城市交通,2014,12(3): 66-74

    WANG Lianzhen, PEI Yulong. Driving fatigue recognition model based on bayesian network[J]. Urban Transport of China, 2014, 12(3): 66-74
    李家文,成波. 驾驶人状态适应式疲劳预警方法的研究[J]. 汽车工程,2011,33(8): 694-700

    LI Jiawen, CHENG Bo. A study on the adaptive warning method for driving persons fatigue[J]. Automotive Engineering, 2011, 33(8): 694-700
    胥川,王雪松,陈小鸿,等. 基于决策树的驾驶疲劳等级分析与判定[J]. 同济大学学报(自然科学版),2015,43(1): 75-81

    XU Chuan, WANG Xuesong, CHEN Xiaohong, et al. Driver drowsiness level analysis and prediction based on decision tree[J]. Journal of Tongji University (Natural Science), 2015, 43(1): 75-81
    DINGES D F, GRACE R. PERCLOS: A valid psychophysiological measure of alertness as assessed by psychomotor vigilance[R]. Washington D. C.: US Federal Highway Administration, 1998
    胥川. 疲劳驾驶行为特征及提示有效性研究[D]. 上海: 同济大学, 2014
    肖献强,殷延杰,王家恩. 基于个体特性的驾驶行为操纵模式建模方法[J]. 中国机械工程,2016,27(19): 2681-2686,2692 doi: 10.3969/j.issn.1004-132X.2016.19.021

    XIAO Xianqiang, YIN Yanjie, WANG Jiaen. Driving behavior operation pattern modeling method based on individual characteristics[J]. China Mechanical Engineering, 2016, 27(19): 2681-2686,2692 doi: 10.3969/j.issn.1004-132X.2016.19.021
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