Analysis of EEG characteristics of drivers and driving safety in undersea tunnel
To study the influence of the driving environment of an undersea tunnel on driver EEG (electroencephalography) characteristics and driving safety, a real vehicle experiment was performed in the Qingdao Jiaozhou Bay Tunnel. The experimental data of the drivers' real vehicle experiment were colle...
Saved in:
Main Authors: | , , , |
---|---|
Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2022
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/154038 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-154038 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-1540382022-06-08T01:25:15Z Analysis of EEG characteristics of drivers and driving safety in undersea tunnel Yang, Yongzheng Du, Zhigang Jiao, Fangtong Pan, Fuquan School of Civil and Environmental Engineering Engineering::Civil engineering Undersea Tunnel Illuminance To study the influence of the driving environment of an undersea tunnel on driver EEG (electroencephalography) characteristics and driving safety, a real vehicle experiment was performed in the Qingdao Jiaozhou Bay Tunnel. The experimental data of the drivers' real vehicle experiment were collected using an illuminance meter, EEG instrument, video recorder and other experimental equipment. The undersea tunnel is divided into different areas, and the distribution law of driving environment characteristics, EEG characteristics and vehicle speed characteristics is analyzed. The correlations between the driving environment characteristics, EEG characteristics and vehicle speed characteristics model the variables that pass the correlation test. The driving safety evaluation model of an undersea tunnel is established, and the driving safety in different areas of the undersea tunnel is evaluated. The results show that there are obvious differences in illumination, EEG power change rate, vehicle speed and other variables in different areas of the undersea tunnel. The driving environment characteristics are highly correlated with the β wave power change rate. The driving safety of different areas of the undersea tunnel from high to low is: upslope area, downslope area, exit area and entrance area. The study will provide a theoretical basis for the safe operation of the undersea tunnel. Published version This research was funded by Fundamental Research Funds for the Central Universities, grant number 2020-YB-018, National Natural Science Foundation of China, grant number 52072291, and Shandong Provincial Natural Science Foundation of China, grant number ZR2020MG021. 2022-06-08T01:25:15Z 2022-06-08T01:25:15Z 2021 Journal Article Yang, Y., Du, Z., Jiao, F. & Pan, F. (2021). Analysis of EEG characteristics of drivers and driving safety in undersea tunnel. International Journal of Environmental Research and Public Health, 18(18), 9810-. https://dx.doi.org/10.3390/ijerph18189810 1660-4601 https://hdl.handle.net/10356/154038 10.3390/ijerph18189810 34574749 2-s2.0-85115075709 18 18 9810 en International Journal of Environmental Research and Public Health © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). application/pdf |
institution |
Nanyang Technological University |
building |
NTU Library |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
NTU Library |
collection |
DR-NTU |
language |
English |
topic |
Engineering::Civil engineering Undersea Tunnel Illuminance |
spellingShingle |
Engineering::Civil engineering Undersea Tunnel Illuminance Yang, Yongzheng Du, Zhigang Jiao, Fangtong Pan, Fuquan Analysis of EEG characteristics of drivers and driving safety in undersea tunnel |
description |
To study the influence of the driving environment of an undersea tunnel on driver EEG (electroencephalography) characteristics and driving safety, a real vehicle experiment was performed in the Qingdao Jiaozhou Bay Tunnel. The experimental data of the drivers' real vehicle experiment were collected using an illuminance meter, EEG instrument, video recorder and other experimental equipment. The undersea tunnel is divided into different areas, and the distribution law of driving environment characteristics, EEG characteristics and vehicle speed characteristics is analyzed. The correlations between the driving environment characteristics, EEG characteristics and vehicle speed characteristics model the variables that pass the correlation test. The driving safety evaluation model of an undersea tunnel is established, and the driving safety in different areas of the undersea tunnel is evaluated. The results show that there are obvious differences in illumination, EEG power change rate, vehicle speed and other variables in different areas of the undersea tunnel. The driving environment characteristics are highly correlated with the β wave power change rate. The driving safety of different areas of the undersea tunnel from high to low is: upslope area, downslope area, exit area and entrance area. The study will provide a theoretical basis for the safe operation of the undersea tunnel. |
author2 |
School of Civil and Environmental Engineering |
author_facet |
School of Civil and Environmental Engineering Yang, Yongzheng Du, Zhigang Jiao, Fangtong Pan, Fuquan |
format |
Article |
author |
Yang, Yongzheng Du, Zhigang Jiao, Fangtong Pan, Fuquan |
author_sort |
Yang, Yongzheng |
title |
Analysis of EEG characteristics of drivers and driving safety in undersea tunnel |
title_short |
Analysis of EEG characteristics of drivers and driving safety in undersea tunnel |
title_full |
Analysis of EEG characteristics of drivers and driving safety in undersea tunnel |
title_fullStr |
Analysis of EEG characteristics of drivers and driving safety in undersea tunnel |
title_full_unstemmed |
Analysis of EEG characteristics of drivers and driving safety in undersea tunnel |
title_sort |
analysis of eeg characteristics of drivers and driving safety in undersea tunnel |
publishDate |
2022 |
url |
https://hdl.handle.net/10356/154038 |
_version_ |
1735491157611249664 |