基于智能手环的愤怒驾驶行为动态检测方法

doi:10.16265/j.cnki.issn1003-3033.2022.S1.0644

中国安全科学学报 ›› 2022, Vol. 32 ›› Issue (S1): 178-183.doi: 10.16265/j.cnki.issn1003-3033.2022.S1.0644

基于智能手环的愤怒驾驶行为动态检测方法

牛世峰¹(), 马彬涛², 刘彦君², 郝帅洁²

¹ 长安大学汽车运输安全保障技术交通行业重点实验室, 陕西西安 710064
² 长安大学汽车学院, 陕西西安 710064

收稿日期:2022-02-13 修回日期:2022-04-10 出版日期:2022-06-30 发布日期:2022-12-30
作者简介:
牛世峰 (1982—),男,山西忻州人,工学博士,教授,主要从事交通安全、智能交通、驾驶人行为分析等方面的研究。E-mail: nsf530@chd.edu.cn。
基金资助:
国家重点研发计划项目(2019YFB1600500)

A smart bracelet-based method for dynamic detection of angry driving behaviors

NIU Shifeng¹(), MA Bintao², LIU Yanjun², HAO Shuaijie²

¹ Key Laboratory of Automotive Transportation Safety Assurance Technology for Transportation Industry, Chang'an University, Xi'an Shaanxi 710064, China
² School of Automobile, Chang'an University, Xi'an Shaanxi 710064, China

Received:2022-02-13 Revised:2022-04-10 Online:2022-06-30 Published:2022-12-30

摘要/Abstract

摘要：

为解决驾驶人因愤怒驾驶而导致交通事故的问题,首先,聘请18名职业驾驶人佩戴智能手环开展实车试验,采集驾驶人的心电指标;然后,经统计检验发现不同愤怒情绪强度下心电指标心率 (HR)、RR间期的平均值 (RRmean)、RR间期的标准差 (SDNN)、连续差的均方根 (RMSSD)、RR间期大于50 ms的个数 (PNN50)、高频 (HF)、非线性指标(SD1、SD2、SD2/SD1)具有显著差异;最后,分别以三级愤怒驾驶行为(正常、轻微愤怒、强烈愤怒)和二级愤怒驾驶行为(正常和愤怒)为因变量,以显著差异心电指标为自变量,基于支持向量机(SVM)、K近邻(KNN)和线性分析(LD)建立驾驶人愤怒驾驶行为动态检测模型。结果表明:二级愤怒驾驶行为识别模型识别效果明显优于三级愤怒驾驶行为识别模型;二级愤怒驾驶行为识别模型中SVM效果最好,三级愤怒驾驶行为识别模型LD模型识别性能最佳。

关键词: 智能手环, 愤怒驾驶, 检测指标, 心电信号, 情绪识别

Abstract:

In order to prevent traffic accidents caused by angry driving, 18 professional drivers were employed for real-world tests where they their electrocardiogram indicators were collected through the smart bracelets they wore. Then, it was found in statistical tests that electrocardiogram indicators heart rate (HR), mean of RR intervals (RRmean), standard deviation of RR intervals (SDNN), root mean square of continuous difference (RMSSD), number of RR intervals greater than 50ms (PNN50), high frequency (HF) and non-linear indicators (SD1, SD2, SD2/SD1) were significantly different. Finally, with tertiary angry driving behaviors (normal, mildly angry, and strongly angry) and secondary ones (normal and angry) as dependent variables and significantly different electrocardiogram indicators as independent ones respectively, a dynamic detection model of drivers' angry driving behavior was developed based on support vector machine (SVM), K-nearest neighbor (KNN) and linear analysis (LD). The results show that the model's recognition effect for secondary angry driving behaviors was greatly better than that for third-level behavior recognition, and the SVM presents the best performance in the second-level angry driving behavior recognition model, while LD model is the best in the third-level recognition one.

Key words: smart bracelet, angry driving, testing index, electrocardiogram signal, emotion recognition

牛世峰, 马彬涛, 刘彦君, 郝帅洁. 基于智能手环的愤怒驾驶行为动态检测方法[J]. 中国安全科学学报, 2022, 32(S1): 178-183.

NIU Shifeng, MA Bintao, LIU Yanjun, HAO Shuaijie. A smart bracelet-based method for dynamic detection of angry driving behaviors[J]. China Safety Science Journal, 2022, 32(S1): 178-183.

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参考文献 15

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特征类型	特征名称与定义	单位
心率	HR:心率	次/min
时域特征	RRmean:RR间期均值	ms
	SDNN:RR间期标准差	ms
	RMSSD:RR间期差值均方根	ms
	PNN50:RR间期大于50ms的个数	次
频域特征	LF(低频功率):功率谱密度曲线函数在0.04~0.15 Hz范围内的积分值	ms²
频域特征	HF(高频功率):功率谱密度曲线函数在0.15~0.4 Hz范围内的积分值	ms²
非线性指标	SD1:垂直于标识线点的标准偏差	—
	SD2:同一条直线的标准偏差	—
	SD2/SD1:横纵标准偏差比值	—

指标	卡方	自由度	显著性
HR/(次·min^-1)	216.093	2	0.000
RRmean/ms	216.891	2	0.000
SDNN/ms	28.395	2	0.000
RMSSD/ms	73.569	2	0.000
PNN50/次	133.635	2	0.000
LF	1.979	2	0.372
HF	89.099	2	0.000
SD1	68.64	2	0.000
SD2	40.772	2	0.000
SD2/SD1	36.407	2	0.000

指标	正常情绪- 轻微愤怒	正常情绪- 强烈愤怒	轻微愤怒- 强烈愤怒
HR/(次·min^-1)	0.000	0.000	0.000
RRmean/ms	0.000	0.000	0.000
SDNN/ms	0.000	0.000	0.829
RMSSD/ms	0.000	0.000	0.890
PNN50/次	0.000	0.000	0.673
HF	0.000	0.000	0.195
SD1	0.000	0.000	0.056
SD2	0.000	0.000	0.697
SD2/SD1	0.000	0.000	0.256

指标	SVM			KNN			LD
指标	轻微	正常	强烈	轻微	正常	强烈	轻微	正常	强烈
TPR	0.563	0.974	0.954	0.563	0.944	0.943	0.531	0.969	0.977
PR	0.667	0.946	0.965	0.563	0.939	0.854	0.773	0.945	0.955
F1	0.610	0.960	0.960	0.563	0.941	0.896	0.630	0.957	0.966
FPR	0.032	0.098	0.014	0.050	0.107	0.065	0.018	0.097	0.019

指标	SVM		KNN		LD
指标	二级愤怒	三级愤怒	二级愤怒	三级愤怒	二级愤怒	三级愤怒
TPR	0.990	0.830	0.995	0.816	0.969	0.826
FPR	0.118	0.048	0.185	0.074	0.101	0.045
PR	0.933	0.859	0.899	0.785	0.941	0.891
F1	0.960	0.843	0.944	0.800	0.955	0.851
AUC	0.980	0.970	0.980	0.920	0.990	0.970
ACC	0.949	0.827	0.927	0.905	0.943	0.924

基于智能手环的愤怒驾驶行为动态检测方法

A smart bracelet-based method for dynamic detection of angry driving behaviors

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