CR-TMS: Connected Vehicles enabled Road Traffic Congestion Mitigation System using Virtual Road Capacity Inflation

S. Djahel, Y. H. Aoul, Renan Pincemin
{"title":"CR-TMS: Connected Vehicles enabled Road Traffic Congestion Mitigation System using Virtual Road Capacity Inflation","authors":"S. Djahel, Y. H. Aoul, Renan Pincemin","doi":"10.1109/ITSC45102.2020.9294521","DOIUrl":null,"url":null,"abstract":"Road traffic management experts are constantly striving to develop, implement, and test a number of novel strategies to reduce traffic congestion impact on the economy, society, and the environment. Despite their efforts, these strategies are still inefficient and a call for advanced multidisciplinary approaches is needed. We, therefore, introduce in this paper an original traffic congestion mitigation strategy inspired by a well-known technology in wireless communications, i.e. cognitive radio technology. Our strategy exploits Connected Vehicles technology along with the often under-utilized reserved lanes, such as bus and carpool lanes, to virtually inflate the road network capacity to ease traffic congestion situations. Two variants of our strategy have been evaluated using simulation and the obtained results are very promising in terms of the achieved reduction in average travel time for different vehicle classes including buses as well.","PeriodicalId":394538,"journal":{"name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","volume":"35 10","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITSC45102.2020.9294521","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Road traffic management experts are constantly striving to develop, implement, and test a number of novel strategies to reduce traffic congestion impact on the economy, society, and the environment. Despite their efforts, these strategies are still inefficient and a call for advanced multidisciplinary approaches is needed. We, therefore, introduce in this paper an original traffic congestion mitigation strategy inspired by a well-known technology in wireless communications, i.e. cognitive radio technology. Our strategy exploits Connected Vehicles technology along with the often under-utilized reserved lanes, such as bus and carpool lanes, to virtually inflate the road network capacity to ease traffic congestion situations. Two variants of our strategy have been evaluated using simulation and the obtained results are very promising in terms of the achieved reduction in average travel time for different vehicle classes including buses as well.
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
CR-TMS:使用虚拟道路容量膨胀的联网车辆道路交通拥堵缓解系统
道路交通管理专家正在不断努力开发、实施和测试一些新的策略,以减少交通拥堵对经济、社会和环境的影响。尽管他们做出了努力,但这些策略仍然效率低下,需要采用先进的多学科方法。因此,我们在本文中引入了一种新颖的交通拥堵缓解策略,该策略的灵感来自于无线通信中的一种知名技术,即认知无线电技术。我们的策略是利用互联汽车技术以及经常未被充分利用的预留车道,如公共汽车和拼车车道,来增加道路网络的容量,以缓解交通拥堵情况。我们的策略的两种变体已经使用模拟进行了评估,所获得的结果在减少不同类别的车辆(包括公共汽车)的平均旅行时间方面非常有希望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
CR-TMS: Connected Vehicles enabled Road Traffic Congestion Mitigation System using Virtual Road Capacity Inflation A novel concept for validation of pre-crash perception sensor information using contact sensor Space-time Map based Path Planning Scheme in Large-scale Intelligent Warehouse System Weakly-supervised Road Condition Classification Using Automatically Generated Labels Studying the Impact of Public Transport on Disaster Evacuation
×
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