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  • 标题:Decentralized State-Observer-Based Traffic Density Estimation of Large-Scale Urban Freeway Network by Dynamic Model
  • 本地全文:下载
  • 作者:Yuqi Guo
  • 期刊名称:Information
  • 电子版ISSN:2078-2489
  • 出版年度:2017
  • 卷号:8
  • 期号:3
  • 页码:95
  • DOI:10.3390/info8030095
  • 语种:English
  • 出版社:MDPI Publishing
  • 摘要:In order to estimate traffic densities in a large-scale urban freeway network in an accurate and timely fashion when traffic sensors do not cover the freeway network completely and thus only local measurement data can be utilized, this paper proposes a decentralized state observer approach based on a macroscopic traffic flow model. Firstly, by using the well-known cell transmission model (CTM), the urban freeway network is modeled in the way of distributed systems. Secondly, based on the model, a decentralized observer is designed. With the help of the Lyapunov function and S-procedure theory, the observer gains are computed by using linear matrix inequality (LMI) technique. So, the traffic densities of the whole road network can be estimated by the designed observer. Finally, this method is applied to the outer ring of the Beijing’s second ring road and experimental results demonstrate the effectiveness and applicability of the proposed approach.
  • 关键词:urban freeway network; traffic densities estimation; decentralized state observer; Lyapunov function; S-procedure urban freeway network ; traffic densities estimation ; decentralized state observer ; Lyapunov function ; S-procedure
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