|Table of Contents|

Analysis of the influence of longitudinal slope changes of undersea tunnels on drivers’ EEG signals(PDF)

Journal of Shenzhen University Science and Engineering[ISSN:1000-2618/CN:44-1401/N]

Issue:
2022 Vol.39 No.3(237-362)
Page:
271-277
Research Field:
Transportation Logistics

Info

Title:
Analysis of the influence of longitudinal slope changes of undersea tunnels on drivers’ EEG signals
Author(s):
YANG Yongzheng1PAN Fuquan1WANG Zhaoqiang2ZHANG Lixia1and YANG Jinshun1
1) School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266520, Shandong Province, P.R.China
2) Qingdao Municipal Engineering Design and Research Institute, Qingdao 266100, Shandong Province, P.R.China
Keywords:
highway transportation undersea tunnel longitudinal slope driver electroencephalography brain region driving safety
PACS:
U491.3
DOI:
10.3724/SP.J.1249.2022.03271
Abstract:
In order to clarify the impact of changes in the longitudinal slope of undersea tunnel on the driver’s electroencephalography (EEG) signal, real vehicle experiments are carried out, using EEG instrument, gradient recorder, video recorder and other experimental equipments to collect data, such as driver’s EEG and the data on the longitudinal slope of the undersea tunnel. The EEG power spectrum and EEG power are selected as parameters, and the EEG signal change law is analyzed when the driver passes through the undersea tunnel’s slope change area; the slope change areas are grouped according to the difference of the up and down slopes, and the mathematical models of the longitudinal slope change and the change of EEG β wave power have been established respectively. The study results show that the brain activity level of drivers increases significantly when passing through the gradient zone; the frontal area is the brain area which is most sensitive to the changes in longitudinal slope; the longitudinal slope and its change are positively correlated with the change of the driver’s EEG β wave power. The smaller the longitudinal slope, the smaller the EEG β wave power change; the lower the driver’s psychological pressure, the better the driving safety.

References:

[1] 曲立清,李翔,代镇洋. 青岛胶州湾海底跨海通道及前海沿线地下道路工程[J]. 隧道建设,2020,40(6):905-924.
QU Liqing, LI Xiang, DAI Zhenyang. Qingdao Jiaozhou Bay undersea cross-sea passage and underground road project along the front sea [J]. Tunnel Construction, 2020, 40(6): 905-924.(in Chinese)
[2] SONG Chaoye, ZHOU Shuming. The overall design of Qingdao Jiaozhou Bay subsea tunnel [J]. Advanced Materials Research, 2012, 368(10): 2971-2976.
[3] 王健. V型海底隧道交通流运行特性及其模型研究[D].青岛:青岛理工大学,2018.
WANG Jian. Study on traffic flow characteristics and its model of V-shaped subsea tunnel [D]. Qingdao: Qingdao University of Technology, 2018.(in Chinese)
[4] ZHOU Hong, ZHAO Yinghui, SHEN Qiang, et al. Risk assessment and management via multi-source information fusion for undersea tunnel construction [J]. Automation in Construction, 2020, 111(3): 103050.
[5] PAN Fuquan, ZHANG Lixia, WANG Jian, et al. Lane-changing risk analysis in undersea tunnels based on fuzzy inference [J]. IEEE Access, 2020, 8(1): 19512-19520.
[6] 冯忠祥,杨苗苗,马昌喜,等. 城市下穿隧道纵坡坡度和速度对驾驶人心率增长率的影响[J]. 中国公路学报,2018,31(4):66-77.
FENG Zhongxiang, YANG Miaomiao, MA Changxi, et al. Influence of longitudinal slope of urban underpass tunnel on driver’s heart rate growth rate [J]. Chinese Journal of Highway and Transport, 2018, 31(4): 66-77.(in Chinese)
[7] 张志刚,胡金平,刘洪洲,等. 水下公路隧道最大纵坡取值研究[J]. 现代隧道技术,2013,50(4):8-14.
ZHANG Zhigang, HU Jinping, LIU Hongzhou, et al. Study on maximum longitudinal slope of underwater highway tunnel [J]. Modern Tunnelling Technology, 2013, 50(4): 8-14.(in Chinese)
[8] 赵建有,何操,郑明明. 高速公路隧道纵坡对驾驶人心率的影响[J]. 长安大学学报自然科学版,2010,30(2):80-83,100.
ZHAO Jianyou, HE Cao, ZHENG Mingming. Influence of longitudinal slope of expressway tunnel on driver’s heart rate [J]. Journal of Chang’an University Natural Science Edition, 2010, 30(2): 80-83, 100.(in Chinese)
[9] 莫秋云,李荣敬,李军,等. 基于ECG指标的山区公路线形对驾驶员特性的影响研究[J]. 中国安全科学学报,2013,23(12):16-20.
MO Qiuyun, LI Rongjing, LI Jun, et al. Research on the influence of mountain highway alignment on driver characteristics based on ECG index [J]. Chinese Safety Science Journal, 2013, 23(12): 16-20. (in Chinese)
[10] 周书明. 青岛胶州湾海底隧道总体设计与施工[J]. 隧道建设,2013,33(1):38-44.
ZHOU Shuming. Overall design and construction of Qingdao Jiaozhou Bay Subsea Tunnel [J]. Tunnel Construction, 2013, 33(1): 38-44.(in Chinese)
[11] YANG Liu, GUAN Wei, MA Rui, et al. Comparison among driving state prediction models for car-following condition based on EEG and driving features [J]. Accident Analysis and Prevention, 2019, 133(10): 105296.
[12] 朱守林,赵谦,戚春华,等. 草原公路交通标志信息量对驾驶员脑电信号的影响分析[J]. 科学技术与工程,2020,20(20):8407-8412.
ZHU Shoulin, ZHAO Qian, QI Chunhua, et al. Analysis of the influence of traffic sign information on driver’s EEG signal on grassland road [J]. Science Technology and Engineering, 2020, 20(20): 8407-8412.(in Chinese)
[13] PAN Fuquan, YANG Yongzheng, ZHANG Lixia, et al. Analysis of EEG characteristics of drivers at the entrance and exit of an undersea tunnel and research on driving safety [J]. International Journal of Safety and Security Engineering, 2021, 11(2): 155-165.
[14] 焦方通,杜志刚,王首硕,等. 城市水下特长隧道弯道驾驶人扫视行为研究[J].中国安全科学学报,2019,29(7):104-109.
JIAO Fangtong, DU Zhigang, WANG Shoushuo, et al. Research on the scanning behavior of drivers on curved road in urban underwater extra-long tunnel [J]. Chinese Safety Science Journal, 2019, 29(7): 104-109.(in Chinese)

Memo

Memo:
-