基于样本熵的分心驾驶心理反应研究
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摘要
分心驾驶.从生理角度反应具有一定的准确度,而心电信号作为反映生理指标的参数具有较好的应用性.本文通过了解驾驶员在分心行驶状况下对心率(HR)以及心电变异率(HRV)的影响,通过样本熵计算混乱程度,研究了基于样本熵的分心驾驶心电反应情况.结果表明,在分心驾驶过程中,HRV比HR更能表现分心的心电变化情况,且在不同分心任务情况下,发送微信短信时驾驶员心电混乱程度即危险程度最高,其样本熵值达到0. 11.论文研究了分心状况下的驾驶员生理反应特征,为深化分心驾驶判定提供了支持,也为研究驾驶员心理特征提供了研究思路.
The impact of driving distraction on driver's behavior has been one of the important directions of driving distraction research. The ECG signal has good applicability to reflect the physiological index.Therefore,this paper investigates the method of driving behavior during distraction by detecting Heart Rate( HR) and Heart Rate Variability( HRV) of driver in different driving conditions,under which an analysis is conducted based on sample entropy. The results show that HRV is more effective than HR in detecting driving distractions. In different distracting tasks,the degree of ECG confusion is the highest when drivers text while driving. The highest degree of danger occurs when the sample entropy reaches0. 11. This paper examines the driver ' s physiological response, supporting for driving distraction judgment,which provides a good research idea for the driver's psychological research.
The impact of driving distraction on driver's behavior has been one of the important directions of driving distraction research. The ECG signal has good applicability to reflect the physiological index.Therefore,this paper investigates the method of driving behavior during distraction by detecting Heart Rate( HR) and Heart Rate Variability( HRV) of driver in different driving conditions,under which an analysis is conducted based on sample entropy. The results show that HRV is more effective than HR in detecting driving distractions. In different distracting tasks,the degree of ECG confusion is the highest when drivers text while driving. The highest degree of danger occurs when the sample entropy reaches0. 11. This paper examines the driver ' s physiological response, supporting for driving distraction judgment,which provides a good research idea for the driver's psychological research.
引文
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[18]HE Weixing,CHEN Xiaoping,SHAO Junting.Sleep EEG staging based on sample entropy[J].Journal of Jiangsu University,2009,30(5):501-504.
[19]钟运健.心率变异率在运动性疲劳诊断应用的实验研究[D].南昌:江西师范大学体育学院,2004.
[2]Yerkes R M,Dodson J D.The relation of strength of stimulus to rapidity of habit-ormation[J].Journal of comparative neurology and psychology,1908,18(5):459-482.
[3]Wu Qun.An overview of driving distraction measure methods[J].Institute of Electrical and Electronics Engineers,2009(53):78-83.
[4]Lee J D,Strayer D L.Preface to a special section on driver distraction[J].Human Factors,2004,46(4):583-586.
[5]Wu Qun.An overview of driving distraction measure methods[J].Institute of Electrical and Electronics Engineers,2009(53):78-83.
[6]Sheridan T B.Big research brother as driver:New demands and problems for the man at the wheel[J].Human Factors,1970,12(1):95-101.
[7]Michon J A.Explanatory pitfalls and rule-based driver models[J].Accident Analysis and Prevention,1989,21(4):341-353.
[8]Ranney T A.Models of driving behavior-a review of their evolution[J].Accident analysis and Prevention,1994,26(6):733-750.
[9]Dingus T A,Klauer S G,Neale V L,et a1.The 100 car naturalistic driving study,phase II-results of the100ear field experiment(Report No.DOT HS810593)[R].Washington,D.C:National Highway Traffic Safety Administration,2006.
[10]霍克.城市道路驾驶员车道变换行为及注视转移特性研究[D].西安:长安大学,2010.
[11]Alm H,Nilsson L.Changes in driver behavior as a function of hands-free mobile telephones.A simulator study.Accident&Analysis and Prevention,1994,26(4):441-451.
[12]Burns P C,Lansdown T C.E-distraction:The challengers for safe and useable internet services in vehicles.On-line paper.Available at www.nrd.nhtsa.dot.gov/departments/nrd-13/driver-distraction/welcome.htm 2000.
[13]Liu Bor-Shong,Lee Yung Hu.In vehicle workload assessment:effeet of traffic situations and cellular telephone use[J].Joumal of Safety Researeh,2006,37(1):99-10.
[14]Matthews R,Legg S,Charlton S.The effect of cell phone type on driver subjective workload during concurrent driving and conversing[J].Accident Analysis and Prevention,2003,35:441-450.
[15]李平凡,王殿海,刘东波.驾驶中拨打手机对驾驶人脑力负荷及驾驶行为的影响分析[J].交通信息与安全,2010,25(156):103-107.
[16]Joshua S.Richman.Physiological time-series analysis using approximate entropy and sample entropy[J].JPhysiol Heart Circ Physiol,2000,278:2039-2049.
[17]赵晓华,许士丽,荣建.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.
[18]HE Weixing,CHEN Xiaoping,SHAO Junting.Sleep EEG staging based on sample entropy[J].Journal of Jiangsu University,2009,30(5):501-504.
[19]钟运健.心率变异率在运动性疲劳诊断应用的实验研究[D].南昌:江西师范大学体育学院,2004.