基于心率变异性的高密度立交出入口驾驶人精神负荷特性

牟俊龙; 杨迪; 矫成武; 孔繁星; 陈正欢; 徐进

doi:10.3963/j.jssn.1674-4861.2024.01.004

基于心率变异性的高密度立交出入口驾驶人精神负荷特性

doi: 10.3963/j.jssn.1674-4861.2024.01.004

牟俊龙^1,,
杨迪²,
矫成武³,
孔繁星⁴,
陈正欢¹,
徐进^1, ,

1.
重庆交通大学交通运输学院重庆 400074
2.
余姚市交通规划设计研究院浙江余姚 354001
3.
交通运输部公路科学研究院北京 100088
4.
中铁二院工程集团有限责任公司成都 610031

基金项目:

国家自然科学基金面上项目 52172340

重庆市高校创新研究群体项目 CXQT21022

详细信息

作者简介:
牟俊龙（1999—），硕士研究生. 研究方向：道路交通安全. E-mail: 540542347@qq.com

通讯作者:
徐进（1977—），博士，教授. 研究方向：人-车-路协同、交通环境影响及驾驶行为. E-mail：yhnl_996699@163.com

中图分类号: U491.2
计量
- 文章访问数: 59
- HTML全文浏览量: 36
- PDF下载量: 15
- 被引次数: 0
出版历程
- 收稿日期: 2023-07-25
- 网络出版日期: 2024-05-31

Drivers' Mental Load Characteristics at the Entrance and Exit of High-density Interchanges Based on Heart Rate Variability

1.
School of Traffic & Transportation, Chongqing Jiaotong University, Chongqing, 40074, China
2.
Yu Yao Plan Design & Research Institute of Communications, Yuyao 354001, Zhejiang, China
3.
Research Institute of Highway Ministry of Transport, Beijing 100088, China
4.
China Railway Eryuan Engineering Group Co Ltd, Chengdu 610031, China

摘要

摘要: 互通式立交承担着不同方向交通流的流向转换功能，是道路交通网络的重要节点。目前高密度立交在城市道路网络中已愈发常见，高密度立交之间的间距比普通立交更小，车辆交织更为密集，驾驶人需要在更短的时间内进行分合流驾驶操作。为探究立交间距对驾驶人精神负荷的影响与高密度立交出入口区段的驾驶人精神负荷统计特性，在重庆市内环快速路上选择了1段包含4座连续立交的路段作为实验对象，其中3座立交为高密度立交。通过车载仪器采集47名驾驶人在实车实验过程中的心电数据，对在高密度立交出入口区段与普通间距立交出入口区段的驾驶人心率变异性时域和频域指标进行差异性分析，得到了驾驶人在高密度立交与普通间距立交出入口区段的精神负荷分布特征。研究结果表明：驾驶人在经过普通间距立交出入口区段和高密度立交出入口区段时的心率变异性时域指标不存在显著性差异，频域指标心率变异性的低、高频功率的比值（ratio of low-frequency to high-frequency，LF/HF）存在显著性差异，频域指标LF/HF可作为评价驾驶人精神负荷在立交出入口区段的主要指标；驾驶人在经过高密度立交入口区段时，频域指标LF/HF比经过普通间距立交入口区段时显著增加，立交间距不足会增加驾驶人在立交入口区段的精神负荷；驾驶人在经过普通间距立交出口区段时的心率变异性频域指标LF/HF比经过高密度立交出口区段时显著增加，即驾驶人通过普通间距立交出口区段的精神负荷更大；对于高密度立交群，驾驶人在入口区段的精神负荷水平要略高于出口区段。
- 交通安全 /
- 精神负荷 /
- 心率变异性 /
- 互通立交 /
- 立交群 /
- 出入口 /
- 驾驶行为
Abstract: Interchange bridges serve as important nodes in road traffic networks, facilitating the redirection of traffic flows in different directions. Currently, high-density interchanges are increasingly common in urban road networks. With closer spacing of high-density interchanges compared to regular ones, denser vehicle weaving occurs and drivers are required to perform merging and diverging maneuvers in a shorter time. To investigate the impact of interchange spacing on drivers' mental load and the corresponding statistical characteristics in the entrances and exits of high-density interchanges, a segment of the Inner Ring Expressway in Chongqing with four consecutive interchanges, three of which are high-density interchanges, was selected as the research site. Electrocardiogram data from 47 drivers during on-road experiments were collected using in-vehicle instruments. Differential analysis was conducted on the temporal and spectral indices of driver heart rate variability between the entrances and exits of high-density and regular-spacing interchanges, revealing the distributions of drivers' mental load in these sections. The results indicate that: There is no significant difference in the temporal index of heart rate variability between drivers passing through the entrances and exits of regular-spacing and high-density interchanges. However, there is a significant difference in the spectral index, i.e., the ratio of low-frequency to high-frequency power of heart rate variability (LF/HF), which is believed can serve as the main indicator for evaluating drivers' mental load in interchange entrances and exits. When passing through the entrances of high-density interchanges, the LF/HF significantly increased compared to the one when passing through the entrances of regular-spacing interchanges, indicating that insufficient interchange spacing would increase mental load in the entrances of interchanges. Conversely, the LF/HF is significantly higher when passing through the exits of regular-spacing interchanges than the one when passing through the exits of high-density interchanges, indicating greater mental load when passing through exits of regular-spacing interchanges. For high-density interchanges, drivers' mental load in entrances are slightly higher than that in exits.
- traffic safety /
- mental load /
- heart rate variability /
- interchange /
- interchange group /
- entrance and exit /
- driving behavior

HTML全文

图 1 实验立交与行驶路线

Figure 1. Experimental interchange and driving route

下载: 全尺寸图片幻灯片

图 2 车载仪器和实验车辆

Figure 2. On board instruments and test vehicles

下载: 全尺寸图片幻灯片

图 3 数据截取范围示意图

Figure 3. Schematic diagram of data intercept range

下载: 全尺寸图片幻灯片

图 4 驾驶人HRV指标均值

Figure 4. Average value of drivers' HRV indicators

下载: 全尺寸图片幻灯片

图 5 入口时域指标中位值与均值分布

Figure 5. Median and mean distribution of time domain index at the entrance

下载: 全尺寸图片幻灯片

图 6 入口LF/HF中位值与均值分布

Figure 6. Distribution of median and mean values of entrance LF/HF

下载: 全尺寸图片幻灯片

图 7 出口时域指标中位值与均值分布

Figure 7. Median and mean distribution of exit time domain indicators

下载: 全尺寸图片幻灯片

图 8 出口LF/HF中位值与均值分布

Figure 8. Median and mean distribution of LF/HF at the exit

下载: 全尺寸图片幻灯片

图 9 入口时域指标分布与累计频率曲线

Figure 9. Time domain index distribution and cumulative frequency curve at the entrance

下载: 全尺寸图片幻灯片

图 10 入口频域指标分布与累计频率曲线

Figure 10. Frequency domain index distribution and cumulative frequency curve at the entrance

下载: 全尺寸图片幻灯片

图 11 出口HRV指标分布与累计频率曲线

Figure 11. Distribution and cumulative frequency curve of HRV indicators at the exit

下载: 全尺寸图片幻灯片

图 12 高密度立交出入口时域指标分布曲线

Figure 12. Time domain index distribution curve of small spacing interchange entrance and exit

下载: 全尺寸图片幻灯片

表 1 实验立交基本情况

Table 1. Basic information of experimental interchange

立交名称	立交类型	出入口简称	出入口类型	行驶工况	匝道车道数	主线车道数
人和立交	普通立交	PR1	普通立交入口	主线行驶，途径入口	2	4
		PC1	普通立交出口	由主线驶入匝道	1	4
		GR1	高密度立交入口	由匝道汇入主线	2	4
东环立交	高密度立交	GC1	高密度立交出口	由主线驶入匝道	2	4
		PR2	普通立交入口	由匝道汇入主线	3	4
		PC2	普通立交出口	由主线驶入匝道	2	4
		GR2	高密度立交入口	由匝道汇入主线	2	4
五童立交	高密度立交	GR3	高密度立交入口	主线行驶，途径入口	2	4
		GC2	高密度立交出口	主线行驶，途径出口	1	4
		GC3	高密度立交出口	由主线驶入匝道	2	3
五桂立交	高密度立交	GR4	高密度立交入口	由匝道汇入主线	2	4
五桂立交	高密度立交	GC4	高密度立交出口	由主线驶入匝道	2	4

下载: 导出CSV

表 2 心率变异性指标

Table 2. Heart rate variability metrics

名称	说明
SDNN	所有RR间期标准差，值越小代表人体精神负荷越大
RMSSD	相邻RR间期差值的均方根，值越小代表人体精神负荷越大
LF/HF	低频功率/高频功率，值越大代表人体精神负荷越大

下载: 导出CSV

表 3 立交入口段心率变异性指标非参数检验

Table 3. Nonparametric test of heart rate variability index in the interchange entrance segment

指标	对比工况		R²	DF	渐进显著性
RMSSD	高密度立交入口（匝道）	普通立交入口（匝道）	0.211 09	1	0.645 9
RMSSD	高密度立交入口（主线）	普通立交入口（主线）	0.003 62	1	0.952 0
SDNN	高密度立交入口（匝道）	普通立交入口（匝道）	0.097 4	1	0.755 0
SDNN	高密度立交入口（主线）	普通立交入口（主线）	0.101 88	1	0.749 4
LF/HF	高密度立交入口（匝道）	普通立交入口（匝道）	17.628 66	1	< 0.01
LF/HF	高密度立交入口（主线）	普通立交入口（主线）	0.430 56	1	0.511 71

下载: 导出CSV

表 4 立交出口段心率变异性指标非参数检验

Table 4. Nonparametric test of heart rate variability index in the interchange exit segment

指标	对比工况		卡方	DF	渐进显著性
RMSSD	高密度立交出口（匝道）	普通立交出口（匝道）	0.809 19	1	0.368 36
SDNN	高密度立交出口（匝道）	普通立交出口（匝道）	1.466 54	1	0.225 89
LF/HF	高密度立交出口（匝道）	普通立交出口（匝道）	4.934 09	1	0.026 33

下载: 导出CSV

表 5 立交出入口驾驶人HRV指标特征分位值提取

Table 5. Extraction of driver HRV index characteristic quantile value at interchange entrance and exit

指标	出入口	10^th	15^th	25^th	50^th	75^th	85^th	90^th	95^th	均值
RMSSD/ms	入口	6.00	8.00	11.00	17.00	25.00	29.00	33.00	37.00	18.33
RMSSD/ms	出口	7.00	8.00	11.00	16.00	27.00	31.00	34.00	37.00	18.70
SDNN/ms	入口	10.60	11.84	13.51	20.40	31.12	39.78	45.66	53.11	24.33
SDNN/ms	出口	9.95	11.39	13.87	20.73	29.24	35.74	40.29	40.29	23.71
LF/HF	入口	0.20	0.20	0.40	1.20	2.70	4.00	5.10	6.60	1.97
LF/HF	出口	0.10	0.20	0.40	1.00	2.60	3.90	4.70	6.90	1.91

下载: 导出CSV

参考文献(21)

[1]	黄治炉. 互通式立交设置及出入口研究[D]. 西安: 长安大学, 2016. HUANG Z L. Research on establishment and exit and entrance of interchange bridge[D]. Xi'an: Chang'an University, 2016. (in Chinese)
[2]	胡静. 基于自然驾驶的山地城市立交心理负荷研究[D]. 重庆: 重庆交通大学, 2019. HU J. Research on the psychological load of mountain city interchange based on natural driving. [D]. Chongqing: Chongqing Jiaotong University, 2019. (in Chinese)
[3]	张雪榆, 潘存书, 林伟, 等. 山地城市多车道交织区驾驶人心理负荷研究[J]. 中国安全科学学报, 2022, 32(3): 25-32. https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK202203004.htm ZHANG X Y, PAN C S, LIN W, et al. Psychological load of drivers in multi-lane interweaving areas of urban roads[J]. China Safety Science Journal, 2022, 32(3): 25-32. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK202203004.htm
[4]	吕贞, 戚春华, 朱守林. 草原公路超车工况下驾驶人动态视觉特性及负荷[J]. 中国安全科学学报, 2022, 32(4): 15-22. https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK202204003.htm LYU Z, QI C H, ZHU S L. Dynamic visual characteristics and load of drivers during overtaking maneuvers on prairie highways[J]. China Safety Science Journal, 2022, 32(4): 15-22. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK202204003.htm
[5]	李小菊, 高明星, 方淑艳. 草原公路路域景观对驾驶人心率变异影响研究[J]. 公路, 2022, 67(7): 335-339. https://www.cnki.com.cn/Article/CJFDTOTAL-GLGL202207056.htm LI X J, GAO M X, FANG S Y. Study on the effect of grassland highway landscape on driver's heart rate variability[J]. Highway, 2022, 67(7): 335-339. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-GLGL202207056.htm
[6]	刘敏. 雨雾低能见度环境下基于驾驶人精神负荷的驾驶稳定性状态识别研究[D]. 广州: 华南理工大学, 2017. LIU M. Research on the driving stability state distinguish based on the drivers' mental workload under rain-fog low visibility environment[D]. Guangzhou: South China University of Technology, 2017. (in Chinese)
[7]	KIM M H, SON J. On-road assessment of in-vehicle driving workload for older drivers: design guidelines for intelligent vehicles[J]. International Journal of Automotive Technology, 2011, 12(2): 265-272. doi: 10.1007/s12239-011-0031-y
[8]	CARRY, L, BALDWIN, et al. Dual task assessment of age differences in mental workload with implications for driving[J]. Proceedings of the Human Factors & Ergonomics Society Annual Meeting, 2016, 39(2): 161-171.
[9]	WANG B, ZHANG D, JIN J, et al. Research on the influence of information intensity on driver's mental workload in ITS[C]. The 2002 International Symposium on Safety Science and Technology, Taian, China: COSHA, 2002.
[10]	YANG Y Q, CHEN Y B, WU C X, et al. Effect of highway directional signs on driver mental workload and behavior using eye movement and brain wave[J]. Accident Analysis & Prevention, 2020, 146: 105705-105716.
[11]	徐进, 陈正欢, 廖祺硕, 等. 基于心电数据的高速公路高密度互通立交驾驶负荷研究[J/OL]. (2023-06-09)[2023-7-25]. https://doi.org/10.13229/j.cnki.jdxbgxb.20221522. XU J, CHEN Z H, LIAO Q S, et al. Mental workload of drivers at high-density interchanges of freeways based on ECG data[J/OL]. (2023-06-09)[2023-7-25]. https://doi.org/10.13229/j.cnki.jdxbgxb.20221522.
[12]	刘建蓓, 马小龙, 张志伟, 等. 基于心电分析的青藏高原驾驶人疲劳特性[J]. 交通运输工程学报, 2016, 16(4): 151-158. doi: 10.3969/j.issn.1671-1637.2016.04.016 LIU J B, MA X L, ZHANG Z W, et al. Fatigue characteristics of drivers in Qinghai-Tibet plateau based on ECG analysis[J]. Journal of Transportation Engineering, 2016, 16(4): 151-158. (in Chinese) doi: 10.3969/j.issn.1671-1637.2016.04.016
[13]	林声, 刘建蓓, 阎莹, 等. 基于驾驶负荷的山区高速公路长大下坡路段安全性评价模型[J]. 交通运输工程学报, 2013, 13(6): 99-106. doi: 10.3969/j.issn.1671-1637.2013.06.014 LIN S, LIU J B, YAN Y, et al. Safety evaluation model for long and long downhill sections of mountain expressway based on driving load[J]. Journal of Transportation Engineering, 2013, 13(6): 99-106. (in Chinese) doi: 10.3969/j.issn.1671-1637.2013.06.014
[14]	翟俊达, 鲁光泉, 陈发城, 等. 城市交叉口车路网联信息对青年驾驶人驾驶行为的影响分析[J]. 交通信息与安全, 2022, 40(1): 126-134. doi: 10.3963/j.jssn.1674-4861.2022.01.015 ZHAI J D, LU G Q, CHEN F C, et al. Effects of information from connected vehicles and infrastructure on driving behavior of young drivers at urban intersections[J]. Journal of Transport Information and Safety, 2022, 40(1): 126-134. (in Chinese) doi: 10.3963/j.jssn.1674-4861.2022.01.015
[15]	TOZMAN T, MAGDAS E S, MACDOUGALL H G, et al. Understanding the psychophysiology of flow: a driving simulator experiment to investigate the relationship between flow and heart rate variability[J]. Computers in Human Behavior, 2015, 52: 408-418. doi: 10.1016/j.chb.2015.06.023
[16]	李天彪, 艾力·斯木吐拉. 高原公路驾驶员心率变异性试验分析[J]. 科学技术与工程, 2015, 15(19): 211-216. doi: 10.3969/j.issn.1671-1815.2015.19.043 LI T B, AILI S. Analysis of heart rate variability test for highway drivers at high altitude[J]. Science and Technology and Engineering, 2015, 15(19): 211-216. (in Chinese) doi: 10.3969/j.issn.1671-1815.2015.19.043
[17]	祝荣欣, 王金武. 基于心肌电的联合收获机驾驶人疲劳检测研究[J]. 农机化研究, 2020, 42(2): 8-14, 43. https://www.cnki.com.cn/Article/CJFDTOTAL-NJYJ202002003.htm ZHU R X, WANG J W. Research on fatigue detection of combine harvester driver based on myocardial electricity[J]. Agricultural Mechanization Research, 2020, 42(2): 8-14, 43. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-NJYJ202002003.htm
[18]	赵晓华, 房瑞雪, 荣建, 等. 基于生理信号的驾驶疲劳综合评价方法试验研究[J]. 北京工业大学学报, 2011, 37(10): 1511-1516, 1523. doi: 10.11936/bjutxb2011101511 ZHAO X H, FANG R X, RONG J, et al. Experimental study of a comprehensive evaluation method of driving fatigue based on physiological signals[J]. Journal of Beijing University of Technology, 2011, 37(10): 1511-1516, 1523. (in Chinese) doi: 10.11936/bjutxb2011101511
[19]	於鹏, 严良文, 陈佳乐, 等. 基于心率变异性的人体疲劳度评估模型[J]. 北京生物医学工程, 2021, 40(1): 46-54. YU P, YAN L W, CHEN J L, et al. Assessment model based on heart rate variability for human fatigue[J]. Journal of Beijing University of Technology, 2021, 40(1): 46-54. (in Chinese)
[20]	倪定安, 郭凤香, 周燕宁. 无信号控制交叉口老年驾驶人转向行为图谱研究[J]. 交通信息与安全, 2022, 40(3): 108-117. doi: 10.3963/j.jssn.1674-4861.2022.03.011 NI D A, GUO F X, ZHOU Y N. A graph study on turning behaviors of older drivers at unsignalized intersections[J]. Journal of Transport Information and Safety, 2022, 40(3): 108-117. (in Chinese) doi: 10.3963/j.jssn.1674-4861.2022.03.011
[21]	袁伟, 郭应时, 付锐, 等. 城市道路类型对驾驶人工作负荷的影响[J]. 长安大学学报(自然科学版), 2014, 34(5): 95-100. https://www.cnki.com.cn/Article/CJFDTOTAL-XAGL201405016.htm YUAN W, GUO Y S, FU R, et al. The impact of urban road types on driver workload[J]. Journal of Chang'an University (Natural Science Edition), 2014, 34(5): 95-100. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-XAGL201405016.htm