Incident duration model on urban freeways using Ordered Probit Model

Ruimin Li, Xiaoqiang Zhao, Xinxin Yu, Jianan Zhu, Junwei Li, Nan Cheng
{"title":"Incident duration model on urban freeways using Ordered Probit Model","authors":"Ruimin Li, Xiaoqiang Zhao, Xinxin Yu, Jianan Zhu, Junwei Li, Nan Cheng","doi":"10.1109/ICICIP.2010.5564235","DOIUrl":null,"url":null,"abstract":"Effective traffic incident management requires a full understanding of the various corresponding properties to accurately estimate incident durations and to benefit decision makings of reducing the impact of non-recurring incident relevant congestions. This paper incorporates discrete choice theory in incident duration prediction. Ordered Probit Model is employed to forecast the incident duration. All 62941 incident records from Beijing Transportation Management Bureau are used for model establishment and other 8000 records for validation. The correct estimation ratio of the model is 69.11%, which shows the reliability of the model is rather satisfactory.","PeriodicalId":152024,"journal":{"name":"2010 International Conference on Intelligent Control and Information Processing","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Intelligent Control and Information Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICIP.2010.5564235","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Effective traffic incident management requires a full understanding of the various corresponding properties to accurately estimate incident durations and to benefit decision makings of reducing the impact of non-recurring incident relevant congestions. This paper incorporates discrete choice theory in incident duration prediction. Ordered Probit Model is employed to forecast the incident duration. All 62941 incident records from Beijing Transportation Management Bureau are used for model establishment and other 8000 records for validation. The correct estimation ratio of the model is 69.11%, which shows the reliability of the model is rather satisfactory.
基于有序概率模型的城市高速公路事故持续时间模型
有效的交通事故管理需要充分了解各种相应的属性,以准确估计事故的持续时间,并有利于决策减少非经常性事件相关的交通堵塞的影响。本文将离散选择理论引入到事件持续时间预测中。采用有序概率模型预测事件持续时间。使用北京市交通管理局62941条事故记录进行模型建立,其他8000条记录进行验证。模型的正确估计率为69.11%,表明模型的可靠性令人满意。
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:604180095
Book学术官方微信