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  • 标题:A Multi-class Lane-changing Advisory System for Freeway Merging Sections
  • 本地全文:下载
  • 作者:Salil Sharma ; Ioannis Papamichail ; Ali Nadi
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2021
  • 卷号:54
  • 期号:2
  • 页码:93-98
  • DOI:10.1016/j.ifacol.2021.06.014
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractCooperative intelligent transportation systems (C-ITS) support the exchange of information between vehicles and infrastructure (V2I or I2V). This paper presents an in-vehicle C-ITS application to improve traffic efficiency around a merging section. This application balances the distribution of traffic over the available lanes of a freeway, by issuing targeted lane-changing advice to a selection of vehicles. We add to existing research by embedding multiple vehicle classes in the lane-changing advisory framework. We use a multi-class multi-lane macroscopic traffic flow model to design a feedback-feedforward control law that is based on a linear quadratic regulator (LQR). The performance of the proposed system is evaluated using a microscopic traffic simulator. The results indicate that the lane-changing advisory system is able to suppress Shockwaves in traffic flow and can significantly alleviate congestion. Besides bringing substantial travel time benefits around merging sections of up to nearly 21%, the system dramatically reduces the variance of travel time losses in the system.
  • 关键词:Keywordslane-changing advisoryLQR control methodmerging sectionmulti-classtraffic congestioncooperative intelligent transportation system
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