基于脑电图的新手和有经验驾驶员模拟驾驶过程中制动行为评估

J. Zhang, Gang Guo, Yingzhang Wu, Qiuyang Tang, Changshao Liang
{"title":"基于脑电图的新手和有经验驾驶员模拟驾驶过程中制动行为评估","authors":"J. Zhang, Gang Guo, Yingzhang Wu, Qiuyang Tang, Changshao Liang","doi":"10.1504/ijvp.2020.10033781","DOIUrl":null,"url":null,"abstract":"The driver is an essential factor in the traffic system, and inexperienced drivers are special high-risk groups. We used electroencephalography (EEG) and reaction time to quantify the differences between experienced and novice drivers' risk perception and braking behaviour in a driving simulator. Twenty-seven participants were asked to drive through a 12-km dynamic scenario with EEG signals recorded simultaneously. There are mainly four frequency bands for human EEG activity: alpha, beta, theta, and delta. The power spectral density (PSD) of beta activity was analysed because it dominated when drivers braked in an emergency. The results indicate that the indicators of β activity and reaction time discriminated between the novice and experienced drivers. The reaction time of drivers was related to the increment of the β activity, indicating that the driver's risk perception stage will affect their risk reaction. The study provides us with the operating performance and internal physiological activities of drivers in the braking process.","PeriodicalId":52169,"journal":{"name":"International Journal of Vehicle Performance","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"EEG-based assessment in novice and experienced drivers' braking behaviour during simulated driving\",\"authors\":\"J. Zhang, Gang Guo, Yingzhang Wu, Qiuyang Tang, Changshao Liang\",\"doi\":\"10.1504/ijvp.2020.10033781\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The driver is an essential factor in the traffic system, and inexperienced drivers are special high-risk groups. We used electroencephalography (EEG) and reaction time to quantify the differences between experienced and novice drivers' risk perception and braking behaviour in a driving simulator. Twenty-seven participants were asked to drive through a 12-km dynamic scenario with EEG signals recorded simultaneously. There are mainly four frequency bands for human EEG activity: alpha, beta, theta, and delta. The power spectral density (PSD) of beta activity was analysed because it dominated when drivers braked in an emergency. The results indicate that the indicators of β activity and reaction time discriminated between the novice and experienced drivers. The reaction time of drivers was related to the increment of the β activity, indicating that the driver's risk perception stage will affect their risk reaction. The study provides us with the operating performance and internal physiological activities of drivers in the braking process.\",\"PeriodicalId\":52169,\"journal\":{\"name\":\"International Journal of Vehicle Performance\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Vehicle Performance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/ijvp.2020.10033781\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Vehicle Performance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijvp.2020.10033781","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 1

摘要

驾驶员是交通系统中的一个重要因素,缺乏经验的驾驶员是特殊的高危人群。我们在驾驶模拟器中使用脑电图(EEG)和反应时间来量化经验丰富的驾驶员和新手驾驶员的风险感知和制动行为之间的差异。27名参与者被要求在12公里的动态场景中驾驶,同时记录脑电图信号。人类脑电活动主要有四个频段:阿尔法、贝塔、θ和德尔塔。β活动的功率谱密度(PSD)被分析,因为当驾驶员在紧急情况下刹车时,它占主导地位。结果表明,β活性和反应时间指标在新手和经验丰富的驾驶员之间存在差异。驾驶员的反应时间与β活性的增加有关,表明驾驶员的风险感知阶段会影响其风险反应。该研究为我们提供了驾驶员在制动过程中的操作性能和内部生理活动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
EEG-based assessment in novice and experienced drivers' braking behaviour during simulated driving
The driver is an essential factor in the traffic system, and inexperienced drivers are special high-risk groups. We used electroencephalography (EEG) and reaction time to quantify the differences between experienced and novice drivers' risk perception and braking behaviour in a driving simulator. Twenty-seven participants were asked to drive through a 12-km dynamic scenario with EEG signals recorded simultaneously. There are mainly four frequency bands for human EEG activity: alpha, beta, theta, and delta. The power spectral density (PSD) of beta activity was analysed because it dominated when drivers braked in an emergency. The results indicate that the indicators of β activity and reaction time discriminated between the novice and experienced drivers. The reaction time of drivers was related to the increment of the β activity, indicating that the driver's risk perception stage will affect their risk reaction. The study provides us with the operating performance and internal physiological activities of drivers in the braking process.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
International Journal of Vehicle Performance
International Journal of Vehicle Performance Engineering-Safety, Risk, Reliability and Quality
CiteScore
2.20
自引率
0.00%
发文量
30
期刊最新文献
Six-sigma robust design optimisation of an electric bus considering crashworthiness and lightweight Analytical model for combined ride and handling with leaf spring suspension in commercial vehicles Shifting control optimisation of automatic transmission with congested conditions identification based on the support vector machine Dual evaporator system as an alternative for air-conditioning and refrigeration in automobiles Performance analysis of automotive exhaust muffler characteristics integrating supervised machine learning algorithms
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1