基于移动车辆观测的GPS视频路面缺陷识别

A. Suraji, A. Sudjianto, R. Riman, Candra Aditya, Aviv Yuniar Rahman, Rangga Pahlevi Putra
{"title":"基于移动车辆观测的GPS视频路面缺陷识别","authors":"A. Suraji, A. Sudjianto, R. Riman, Candra Aditya, Aviv Yuniar Rahman, Rangga Pahlevi Putra","doi":"10.1109/ICCoSITE57641.2023.10127782","DOIUrl":null,"url":null,"abstract":"Identification of road surface infrastructure defects is a very important requirement and requires fast and accurate information. The purpose of this study is to identify road surface defects using recording technology with GPS video. The data collection method was carried out by surveying road defects using GPS video with moving car observation. Furthermore, the image data from the video recording is compiled to determine the condition of the road surface damage in accordance with the coordinates of the road segment. The method of analyzing the types of road damage used the Pavement Condition Index (PCI) method, then a roadmap of road damage conditions was made. The research results using GPS video obtained that the percentage of road surface defects for each type of damage is good 10 %, fair 45%, light poor 35% and heavy poor 10%. The results of the identification of road surface defects with GPS video are generally in accordance with the conditions in the field. From the results of this study, it can be recommended that a road defect survey using GPS video can be used as an alternative survey method and has the advantage of being faster.","PeriodicalId":256184,"journal":{"name":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Moving Car Observation (MCO) for Road Surface Defect Identification Using GPS Video\",\"authors\":\"A. Suraji, A. Sudjianto, R. Riman, Candra Aditya, Aviv Yuniar Rahman, Rangga Pahlevi Putra\",\"doi\":\"10.1109/ICCoSITE57641.2023.10127782\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Identification of road surface infrastructure defects is a very important requirement and requires fast and accurate information. The purpose of this study is to identify road surface defects using recording technology with GPS video. The data collection method was carried out by surveying road defects using GPS video with moving car observation. Furthermore, the image data from the video recording is compiled to determine the condition of the road surface damage in accordance with the coordinates of the road segment. The method of analyzing the types of road damage used the Pavement Condition Index (PCI) method, then a roadmap of road damage conditions was made. The research results using GPS video obtained that the percentage of road surface defects for each type of damage is good 10 %, fair 45%, light poor 35% and heavy poor 10%. The results of the identification of road surface defects with GPS video are generally in accordance with the conditions in the field. From the results of this study, it can be recommended that a road defect survey using GPS video can be used as an alternative survey method and has the advantage of being faster.\",\"PeriodicalId\":256184,\"journal\":{\"name\":\"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)\",\"volume\":\"116 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-02-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCoSITE57641.2023.10127782\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Computer Science, Information Technology and Engineering (ICCoSITE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCoSITE57641.2023.10127782","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

路面基础设施缺陷的识别是一个非常重要的要求,需要快速准确的信息。本研究的目的是利用GPS视频记录技术识别路面缺陷。数据采集方法是利用GPS视频测量道路缺陷,并结合移动车辆观测。然后,对视频记录的图像数据进行编译,根据路段坐标确定路面损伤情况。采用路面状况指数(PCI)法对道路损伤类型进行分析,绘制道路损伤状况图。利用GPS视频的研究结果得出,各类损伤中路面缺陷占比为良好10%,一般45%,轻差35%,重差10%。利用GPS视频识别路面缺陷的结果与现场情况基本一致。从本研究的结果来看,可以推荐使用GPS视频进行道路缺陷调查作为一种替代的调查方法,并且具有更快的优点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Moving Car Observation (MCO) for Road Surface Defect Identification Using GPS Video
Identification of road surface infrastructure defects is a very important requirement and requires fast and accurate information. The purpose of this study is to identify road surface defects using recording technology with GPS video. The data collection method was carried out by surveying road defects using GPS video with moving car observation. Furthermore, the image data from the video recording is compiled to determine the condition of the road surface damage in accordance with the coordinates of the road segment. The method of analyzing the types of road damage used the Pavement Condition Index (PCI) method, then a roadmap of road damage conditions was made. The research results using GPS video obtained that the percentage of road surface defects for each type of damage is good 10 %, fair 45%, light poor 35% and heavy poor 10%. The results of the identification of road surface defects with GPS video are generally in accordance with the conditions in the field. From the results of this study, it can be recommended that a road defect survey using GPS video can be used as an alternative survey method and has the advantage of being faster.
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
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