基于模糊的压力感觉水平确定系统的实现与评价:驾驶经验和历史对驾驶员压力的影响

IF 0.7 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Journal of High Speed Networks Pub Date : 2022-08-11 DOI:10.3233/jhs-220693
Kevin Bylykbashi, Ermioni Qafzezi, Phudit Ampririt, Makoto Ikeda, Keita Matsuo, L. Barolli
{"title":"基于模糊的压力感觉水平确定系统的实现与评价:驾驶经验和历史对驾驶员压力的影响","authors":"Kevin Bylykbashi, Ermioni Qafzezi, Phudit Ampririt, Makoto Ikeda, Keita Matsuo, L. Barolli","doi":"10.3233/jhs-220693","DOIUrl":null,"url":null,"abstract":"Drivers are held responsible for the vast majority of traffic accidents. While most of the errors that cause these accidents are involuntary, a significant number of them are caused by irresponsible driving behaviors, which must be utterly preventable. Irresponsible driving, in addition, is often associated with the stress drivers experience while driving. We have previously implemented an intelligent system based on fuzzy logic for determining driver’s stress in Vehicular Ad hoc Networks (VANETs), called Fuzzy-based System for Determining the Stress Feeling Level (FSDSFL), considering the driver’s impatience, the behavior of other drivers, and the traffic condition as input parameters. In this work, we present an Improved FSDSFL (IFSDSFL) system, which considers the driving experience and history as an additional input. We show through simulations the effect that driving experience and history and the other parameters have on the determination of the stress feeling level and demonstrate some actions that can be performed when the stress exceeds certain levels.","PeriodicalId":54809,"journal":{"name":"Journal of High Speed Networks","volume":"1 1","pages":"243-255"},"PeriodicalIF":0.7000,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Implementation and evaluation of a fuzzy-based system for determining stress feeling level in VANETs: Effect of driving experience and history on driver stress\",\"authors\":\"Kevin Bylykbashi, Ermioni Qafzezi, Phudit Ampririt, Makoto Ikeda, Keita Matsuo, L. Barolli\",\"doi\":\"10.3233/jhs-220693\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Drivers are held responsible for the vast majority of traffic accidents. While most of the errors that cause these accidents are involuntary, a significant number of them are caused by irresponsible driving behaviors, which must be utterly preventable. Irresponsible driving, in addition, is often associated with the stress drivers experience while driving. We have previously implemented an intelligent system based on fuzzy logic for determining driver’s stress in Vehicular Ad hoc Networks (VANETs), called Fuzzy-based System for Determining the Stress Feeling Level (FSDSFL), considering the driver’s impatience, the behavior of other drivers, and the traffic condition as input parameters. In this work, we present an Improved FSDSFL (IFSDSFL) system, which considers the driving experience and history as an additional input. We show through simulations the effect that driving experience and history and the other parameters have on the determination of the stress feeling level and demonstrate some actions that can be performed when the stress exceeds certain levels.\",\"PeriodicalId\":54809,\"journal\":{\"name\":\"Journal of High Speed Networks\",\"volume\":\"1 1\",\"pages\":\"243-255\"},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2022-08-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of High Speed Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3233/jhs-220693\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of High Speed Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/jhs-220693","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

摘要

司机应为绝大多数交通事故负责。虽然导致这些事故的大多数错误都是无意识的,但其中很大一部分是由不负责任的驾驶行为造成的,这是完全可以预防的。此外,不负责任的驾驶往往与司机在驾驶时感受到的压力有关。我们之前已经实现了一个基于模糊逻辑的智能系统,用于在车辆自组织网络(VANETs)中确定驾驶员的压力,称为基于模糊的压力感觉水平确定系统(FSDSFL),考虑驾驶员的不耐烦,其他驾驶员的行为以及交通状况作为输入参数。在这项工作中,我们提出了一种改进的FSDSFL (IFSDSFL)系统,该系统将驾驶经验和历史作为额外的输入。我们通过模拟展示了驾驶经验和历史以及其他参数对确定压力感觉水平的影响,并演示了当压力超过一定水平时可以执行的一些操作。
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
Implementation and evaluation of a fuzzy-based system for determining stress feeling level in VANETs: Effect of driving experience and history on driver stress
Drivers are held responsible for the vast majority of traffic accidents. While most of the errors that cause these accidents are involuntary, a significant number of them are caused by irresponsible driving behaviors, which must be utterly preventable. Irresponsible driving, in addition, is often associated with the stress drivers experience while driving. We have previously implemented an intelligent system based on fuzzy logic for determining driver’s stress in Vehicular Ad hoc Networks (VANETs), called Fuzzy-based System for Determining the Stress Feeling Level (FSDSFL), considering the driver’s impatience, the behavior of other drivers, and the traffic condition as input parameters. In this work, we present an Improved FSDSFL (IFSDSFL) system, which considers the driving experience and history as an additional input. We show through simulations the effect that driving experience and history and the other parameters have on the determination of the stress feeling level and demonstrate some actions that can be performed when the stress exceeds certain levels.
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
Journal of High Speed Networks
Journal of High Speed Networks Computer Science-Computer Networks and Communications
CiteScore
1.80
自引率
11.10%
发文量
26
期刊介绍: The Journal of High Speed Networks is an international archival journal, active since 1992, providing a publication vehicle for covering a large number of topics of interest in the high performance networking and communication area. Its audience includes researchers, managers as well as network designers and operators. The main goal will be to provide timely dissemination of information and scientific knowledge. The journal will publish contributed papers on novel research, survey and position papers on topics of current interest, technical notes, and short communications to report progress on long-term projects. Submissions to the Journal will be refereed consistently with the review process of leading technical journals, based on originality, significance, quality, and clarity. The journal will publish papers on a number of topics ranging from design to practical experiences with operational high performance/speed networks.
期刊最新文献
Multitier scalable clustering wireless network design approach using honey bee ratel optimization Transmit antenna selection in M-MIMO system using metaheuristic aided model A comparison study of two implemented fuzzy-based models for decision of logical trust Research on fault detection and remote monitoring system of variable speed constant frequency wind turbine based on Internet of things Efficient dynamic IP datacasting mobility management based on LRS in mobile IP networks
×
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