标题:A probability approach for estimating real-time queue length at lane level
作者:Guo, Yajuan ;Yang, Licai
通讯作者:Yang, Licai
作者机构:[Guo, Yajuan ;Yang, Licai ] School of Control Science and Engineering, Shandong University, Jinan; 250061, China;[Guo, Yajuan ] School of Traffic and 更多
会议名称:2017 Chinese Automation Congress, CAC 2017
会议日期:20 October 2017 through 22 October 2017
来源:Proceedings - 2017 Chinese Automation Congress, CAC 2017
出版年:2017
卷:2017-January
页码:3126-3129
DOI:10.1109/CAC.2017.8243313
关键词:input-output model; lane level; license plate recognition data; probability approach; queue length estimation
摘要:Development of precise active traffic control strategies urgently requires real-time estimation for operational metrics in transportation systems satisfying the level of smaller spatial granularity simultaneously. This paper proposed a probability approach to estimate real-time lane-based queue length using license plate recognition (LPR) data. The method first developed a nested logit model to depict initial lane selection and then improved a lane changing model, which can obtain lane-based equivalent cumulative arrival-departure curve. Thus queue length is obtained combined with input-output model. Finally, validation results show that the proposed approach can capture the real-time variations of queue length and achieve reasonable estimation accuracy for maximum cycle queue length. © 2017 IEEE.
收录类别:EI;SCOPUS
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050262761&doi=10.1109%2fCAC.2017.8243313&partnerID=40&md5=fbabfcc821ae8eb93a48f66c44a7a35c
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