Safety Improvements for Personnel and Vehicles in Short-Term Construction Sites

IF 4.6 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Daniel Rau;Jonas Vogt;Philipp Schorr;Juri Golanov;Andreas Otte;Jens Staub;Horst Wieker
{"title":"Safety Improvements for Personnel and Vehicles in Short-Term Construction Sites","authors":"Daniel Rau;Jonas Vogt;Philipp Schorr;Juri Golanov;Andreas Otte;Jens Staub;Horst Wieker","doi":"10.1109/OJITS.2024.3366708","DOIUrl":null,"url":null,"abstract":"Despite all efforts to enhance safety, construction sites remain a major location for traffic accidents. Short-term construction sites, in particular, face limitations in implementing extensive safety measures due to their condensed timelines. This paper seeks to enhance safety in short-term construction sites by alerting maintenance personnel and approaching vehicles to potentially dangerous scenarios. Focusing on defining the exact dimensions of static construction sites, this method employs high-precision Real-Time-Kinematics-GNSS for localizing traffic cones and deriving the construction site geometry through respective algorithms. By analyzing the geometry, we can identify situations where maintenance personnel are in close proximity to the active lane or when vehicles enter the construction site. To increase awareness of hazardous situations, we present methods for distributing information to maintenance personnel and vehicles, along with technical solutions for warning those involved. Additionally, we discuss the distribution of the construction site’s geometry among approaching vehicles, which can provide future automated vehicles with crucial information on the site’s exact start and end points.","PeriodicalId":100631,"journal":{"name":"IEEE Open Journal of Intelligent Transportation Systems","volume":"5 ","pages":"174-185"},"PeriodicalIF":4.6000,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10439273","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Open Journal of Intelligent Transportation Systems","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10439273/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

Abstract

Despite all efforts to enhance safety, construction sites remain a major location for traffic accidents. Short-term construction sites, in particular, face limitations in implementing extensive safety measures due to their condensed timelines. This paper seeks to enhance safety in short-term construction sites by alerting maintenance personnel and approaching vehicles to potentially dangerous scenarios. Focusing on defining the exact dimensions of static construction sites, this method employs high-precision Real-Time-Kinematics-GNSS for localizing traffic cones and deriving the construction site geometry through respective algorithms. By analyzing the geometry, we can identify situations where maintenance personnel are in close proximity to the active lane or when vehicles enter the construction site. To increase awareness of hazardous situations, we present methods for distributing information to maintenance personnel and vehicles, along with technical solutions for warning those involved. Additionally, we discuss the distribution of the construction site’s geometry among approaching vehicles, which can provide future automated vehicles with crucial information on the site’s exact start and end points.
改善短期施工现场人员和车辆的安全状况
尽管为加强安全做出了种种努力,但建筑工地仍然是交通事故的主要发生地。特别是短期建筑工地,由于时间紧迫,在实施广泛的安全措施方面面临着限制。本文旨在通过提醒维护人员和驶近的车辆注意潜在的危险情况,来加强短期施工现场的安全。该方法侧重于定义静态建筑工地的精确尺寸,采用高精度实时导航卫星系统(Real-Time-Kinematics-GNSS)定位交通锥,并通过相应的算法得出建筑工地的几何形状。通过分析几何图形,我们可以识别出维护人员靠近活动车道或车辆进入施工现场的情况。为了提高对危险情况的认识,我们介绍了向维护人员和车辆发布信息的方法,以及警告相关人员的技术解决方案。此外,我们还讨论了施工现场的几何形状在驶近车辆中的分布情况,这可以为未来的自动驾驶车辆提供有关施工现场确切起点和终点的重要信息。
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 求助全文
来源期刊
CiteScore
5.40
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信