[1]杨永正,潘福全,王召强,等.海底隧道纵坡变化对驾驶人脑电信号影响分析[J].深圳大学学报理工版,2022,39(3):271-277.[doi:10.3724/SP.J.1249.2022.03271]
 YANG Yongzheng,PAN Fuquan,WANG Zhaoqiang,et al.Analysis of the influence of the longitudinal slope change of undersea tunnel on the EEG signals of drivers[J].Journal of Shenzhen University Science and Engineering,2022,39(3):271-277.[doi:10.3724/SP.J.1249.2022.03271]
点击复制

海底隧道纵坡变化对驾驶人脑电信号影响分析()
分享到:

《深圳大学学报理工版》[ISSN:1000-2618/CN:44-1401/N]

卷:
第39卷
期数:
2022年第3期
页码:
271-277
栏目:
交通物流
出版日期:
2022-05-16

文章信息/Info

Title:
Analysis of the influence of the longitudinal slope change of undersea tunnel on the EEG signals of drivers
文章编号:
202203005
作者:
杨永正潘福全王召强张丽霞杨金顺
1)青岛理工大学机械与汽车工程学院,山东青岛 266520;2)青岛市市政工程设计研究院,山东青岛 266100
Author(s):
YANG Yongzheng PAN Fuquan WANG Zhaoqiang ZHANG Lixia and YANG Jinshun
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
关键词:
公路运输海底隧道纵坡驾驶人脑电脑区行车安全
Keywords:
highway transportation undersea tunnel longitudinal slope driver electroencephalography brain region driving safety
分类号:
U491.3
DOI:
10.3724/SP.J.1249.2022.03271
文献标志码:
A
摘要:
为明确海底隧道纵坡坡度变化对驾驶人脑电信号的影响,通过开展实车实验,运用脑电仪、坡度记录仪及录像机等设备,采集车辆通过海底隧道变坡区时,驾驶人的脑电及海底隧道纵坡坡度数据.选取脑电功率谱与脑电功率为参量,分析驾驶人经过海底隧道变坡区时脑电活跃水平的变化规律;按照不同上下坡对变坡区进行分组,分别建立海底隧道纵坡坡度变化与脑电β波功率变化的数学模型.结果表明,驾驶人在经过变坡区时,大脑活跃水平明显提升,额叶区是对纵坡坡度变化最敏感的脑区;纵坡坡度变化与驾驶人脑电β波功率变化正相关,纵坡坡度变化越小,脑电β波功率变化越小,驾驶人心理压力越小,行车安全性越好.
Abstract:
In order to clarify the impact of changes in the longitudinal slope of undersea tunnel on the driver’s EEG (electroencephalography) signals, real vehicle experiments were carried out, using EEG instrument, gradient recorder, video recorder and other experimental equipment to collect data, such as driver’s EEG, the longitudinal slope of the undersea tunnel. The EEG power spectrum and EEG power were selected as parameters, and the EEG signal change law was 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 most sensitive to changes in longitudinal slope; the change of longitudinal slope is positively correlated with the change of β wave power. The longitudinal slope is positively correlated with the driver’s EEG β wave power change. The smaller the longitudinal slope, the smaller the EEG β wave power change, the lower the driver’s psychological pressure, and the better the driving safety.

相似文献/References:

[1]韩彪,聂伟,王卫平,等.基于公交车站的可达性度量模型[J].深圳大学学报理工版,2013,30(No.1(001-110)):98.[doi:10.3724/SP.J.1249.2013.01098]
 Han Biao,Nie Wei,Wang Weiping,et al.Accessibility measurement model based on bus stop[J].Journal of Shenzhen University Science and Engineering,2013,30(3):98.[doi:10.3724/SP.J.1249.2013.01098]
[2]余春晖,黄虹宾.军用车辆离合器半接合点模糊控制试验研究[J].深圳大学学报理工版,2014,31(6):647.[doi:10.3724/SP.J.1249.2014.06647]
 Yu Chunhui and Huang Hongbin.Fuzzy control for half junction point of AMT clutch used on military vehicles[J].Journal of Shenzhen University Science and Engineering,2014,31(3):647.[doi:10.3724/SP.J.1249.2014.06647]
[3]马捷,李津,程琳.客货分离道路系统的车辆分类标准和评价方法[J].深圳大学学报理工版,2015,32(5):524.[doi:10.3724/SP.J.1249.2015.05524]
 Ma Jie,Li Jin,and Cheng Lin.Vehicle classification and evaluation method of separating trucks from passenger vehicles[J].Journal of Shenzhen University Science and Engineering,2015,32(3):524.[doi:10.3724/SP.J.1249.2015.05524]
[4]万霞,黄文伟,强明明.深圳市乘用车道路行驶工况构建[J].深圳大学学报理工版,2016,33(3):281.[doi:10.3724/SP.J.1249.2016.03281]
 Wan Xia,Huang Wenwei,et al.Construction of driving cycle for passenger vehicles in Shenzhen[J].Journal of Shenzhen University Science and Engineering,2016,33(3):281.[doi:10.3724/SP.J.1249.2016.03281]
[5]王长海,肖亮亮.公路选线中的嵌套山体自动提取技术[J].深圳大学学报理工版,2019,36(5):576.[doi:10.3724/SP.J.1249.2019.05576]
 WANG Changhai and XIAO Liangliang.Automatic extraction of nested mountain in highway route selection[J].Journal of Shenzhen University Science and Engineering,2019,36(3):576.[doi:10.3724/SP.J.1249.2019.05576]
[6]奚宽响,查伟雄,等.旅游城镇路网多目标优化模型及算法设计[J].深圳大学学报理工版,2020,37(2):130.[doi:10.3724/SP.J.1249.2020.02130]
 XI Kuanxiang,ZHA Weixiong,LI Jian,et al.Multi-objective optimization model and algorithm design of road network in tourist town[J].Journal of Shenzhen University Science and Engineering,2020,37(3):130.[doi:10.3724/SP.J.1249.2020.02130]
[7]潘福全,邢英,魏金丽,等.基于开放街区的车辆行驶最优路径设计[J].深圳大学学报理工版,2020,37(2):143.[doi:10.3724/SP.J.1249.2020.02143]
 PAN Fuquan,XING Ying,WEI Jinli,et al.Optimal route design of vehicle driving path based on open blocks[J].Journal of Shenzhen University Science and Engineering,2020,37(3):143.[doi:10.3724/SP.J.1249.2020.02143]
[8]张兵,赖冠华,杜媛媛,等.低灯位多维道路照明技术[J].深圳大学学报理工版,2021,38(6):658.[doi:10.3724/SP.J.1249.2021.06658]
 ZHANG Bing,LAI Guanhua,DU Yuanyuan,et al.Multi-dimentional road lighting technology with fixed low-mounting height luminaires[J].Journal of Shenzhen University Science and Engineering,2021,38(3):658.[doi:10.3724/SP.J.1249.2021.06658]

更新日期/Last Update: 2022-05-30