基于工作日交通流量变化的交通时间间隔划分

Yan Yawen, Chen Guojun, Y. Xiaoguang, Wu Zhi-zhou
{"title":"基于工作日交通流量变化的交通时间间隔划分","authors":"Yan Yawen, Chen Guojun, Y. Xiaoguang, Wu Zhi-zhou","doi":"10.1109/ICOIP.2010.115","DOIUrl":null,"url":null,"abstract":"A majority of urban pretimed traffic signal control systems deploy multiple signal time-intervals to account for traffic demand changes during a day. There have been some mature studies on the algorithms of time-intervals split of TOD. However, these algorithms neglected the variation of traffic flow among days of week. In this research, a Nonparametric Test is applied to reflect the variation of traffic flow among days of week and classify the days of week into different categories, and then each day is divided into several timeintervals by adopting an ordered sample cluster algorithm according to the former categories. This method could eliminate the impact of traffic flow uncertainty on the timeintervals split and will provide more accurate time-intervals split for the urban pretimed traffic signal control systems.","PeriodicalId":333542,"journal":{"name":"2010 International Conference on Optoelectronics and Image Processing","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Traffic Time-Intervals Split Based on the Traffic Flow Variation of Days of Week\",\"authors\":\"Yan Yawen, Chen Guojun, Y. Xiaoguang, Wu Zhi-zhou\",\"doi\":\"10.1109/ICOIP.2010.115\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A majority of urban pretimed traffic signal control systems deploy multiple signal time-intervals to account for traffic demand changes during a day. There have been some mature studies on the algorithms of time-intervals split of TOD. However, these algorithms neglected the variation of traffic flow among days of week. In this research, a Nonparametric Test is applied to reflect the variation of traffic flow among days of week and classify the days of week into different categories, and then each day is divided into several timeintervals by adopting an ordered sample cluster algorithm according to the former categories. This method could eliminate the impact of traffic flow uncertainty on the timeintervals split and will provide more accurate time-intervals split for the urban pretimed traffic signal control systems.\",\"PeriodicalId\":333542,\"journal\":{\"name\":\"2010 International Conference on Optoelectronics and Image Processing\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Optoelectronics and Image Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOIP.2010.115\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Optoelectronics and Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOIP.2010.115","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

大多数城市定时交通信号控制系统采用多个信号时间间隔来考虑一天中的交通需求变化。对于TOD的时间间隔分割算法已经有了较为成熟的研究。然而,这些算法忽略了一周中不同天之间交通流量的变化。在本研究中,采用非参数检验方法来反映交通流量在一周中不同日子之间的变化,并将一周中的日子划分为不同的类别,然后根据不同的类别采用有序样本聚类算法将每天划分为多个时间间隔。该方法可以消除交通流不确定性对时间间隔分割的影响,为城市定时交通信号控制系统提供更精确的时间间隔分割。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Traffic Time-Intervals Split Based on the Traffic Flow Variation of Days of Week
A majority of urban pretimed traffic signal control systems deploy multiple signal time-intervals to account for traffic demand changes during a day. There have been some mature studies on the algorithms of time-intervals split of TOD. However, these algorithms neglected the variation of traffic flow among days of week. In this research, a Nonparametric Test is applied to reflect the variation of traffic flow among days of week and classify the days of week into different categories, and then each day is divided into several timeintervals by adopting an ordered sample cluster algorithm according to the former categories. This method could eliminate the impact of traffic flow uncertainty on the timeintervals split and will provide more accurate time-intervals split for the urban pretimed traffic signal control systems.
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:604180095
Book学术官方微信