标题：A probability approach for estimating real-time queue length at lane level
作者：Guo, Yajuan ;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
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.