Utilizing Statistical Techniques in Estimating Uncollected Pavement-Condition Data

M. Hafez, K. Ksaibati, R. Anderson-Sprecher
{"title":"Utilizing Statistical Techniques in Estimating Uncollected Pavement-Condition Data","authors":"M. Hafez, K. Ksaibati, R. Anderson-Sprecher","doi":"10.1061/(ASCE)TE.1943-5436.0000898","DOIUrl":null,"url":null,"abstract":"AbstractThe automated techniques used to collect pavement conditions on county roads are relatively expensive for local agencies. This study evaluates the possibility of reducing the amount of pavement condition data collected in each survey to optimize the costs of data collection. This study applies multiple imputation analyses as an assistant tool to estimate the uncollected condition data at the network level. Another objective of this study is to determine the most cost-effective pavement condition data collection frequencies. By using a case study of secondary paved highways in Wyoming, it was concluded that uncollected condition indices can be predicted using the initial/historical values. The imputation models developed in this paper provide good estimations. Cost analysis of county roads for two counties demonstrates the significant amounts of cost saving when applying the proposed imputation strategy during data collection process. Therefore, pavement condition data is not recommended to be coll...","PeriodicalId":305908,"journal":{"name":"Journal of Transportation Engineering-asce","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Transportation Engineering-asce","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1061/(ASCE)TE.1943-5436.0000898","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

AbstractThe automated techniques used to collect pavement conditions on county roads are relatively expensive for local agencies. This study evaluates the possibility of reducing the amount of pavement condition data collected in each survey to optimize the costs of data collection. This study applies multiple imputation analyses as an assistant tool to estimate the uncollected condition data at the network level. Another objective of this study is to determine the most cost-effective pavement condition data collection frequencies. By using a case study of secondary paved highways in Wyoming, it was concluded that uncollected condition indices can be predicted using the initial/historical values. The imputation models developed in this paper provide good estimations. Cost analysis of county roads for two counties demonstrates the significant amounts of cost saving when applying the proposed imputation strategy during data collection process. Therefore, pavement condition data is not recommended to be coll...
利用统计技术估算未采集路面状况数据
摘要用于采集县域道路路面状况的自动化技术对地方机构来说是相对昂贵的。本研究评估了减少每次调查中收集的路面状况数据量以优化数据收集成本的可能性。本研究将多重归算分析作为辅助工具,在网络层面对未采集状态数据进行估计。本研究的另一个目的是确定最具成本效益的路面状况数据收集频率。通过对怀俄明州二级铺装公路的案例研究,得出未收集状态指数可以使用初始值/历史值进行预测的结论。本文建立的估算模型提供了很好的估计。对两个县县域公路的成本分析表明,在数据收集过程中采用所提出的归算策略可以显著节省成本。因此,路面状况数据不建议冷藏。
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
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