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作者:

Guo, Y. (Guo, Y..) | Chen, Y. (Chen, Y..) | Li, W. (Li, W..) | Zhang, C. (Zhang, C..) (学者:张弛)

收录:

Scopus PKU CSCD

摘要:

In order to timely and accurately estimate traffic densities of the whole road network and to identify congestion in an urban freeway network when traffic sensors do not cover the freeway network completely and only local measurement data can be utilized. A proportional-integral (PI) observer approach was proposed based on a macroscopic traffic flow model. Firstly, the urban freeway network was modeled by embedding the cell transmission model (CTM) into the dynamic graph hybrid automata (DGHA), and then a piecewise affine linear system (PWALS) model was deduced. Moreover, the PI observer was designed on the basis of this model, and the proportional gain and integral gain were computed via using the Linear Matrix Inequality (LMI) method. Especially, the traffic congestion was identified by checking whether the estimated densities were greater than the critical ones. Finally, as examples, the Jingtong freeway and East Third Ring freeway were given to demonstrate the feasibility of the proposed approach. © 2018, Editorial Department of Journal of Beijing University of Technology. All right reserved.

关键词:

Congestion identification; Proportional-integral observer; Traffic density estimation; Urban freeway network

作者机构:

  • [ 1 ] [Guo, Y.]College of Metropolitan Transportation, Beijing University of Technology, Beijing, 100124, China
  • [ 2 ] [Guo, Y.]Beijing Key Laboratory of Transportation Engineering, Beijing, 100124, China
  • [ 3 ] [Guo, Y.]Beijing Collaborative Innovation Center for Metropolitan Transportation, Beijing, 100124, China
  • [ 4 ] [Chen, Y.]College of Metropolitan Transportation, Beijing University of Technology, Beijing, 100124, China
  • [ 5 ] [Chen, Y.]Beijing Key Laboratory of Transportation Engineering, Beijing, 100124, China
  • [ 6 ] [Chen, Y.]Beijing Collaborative Innovation Center for Metropolitan Transportation, Beijing, 100124, China
  • [ 7 ] [Li, W.]College of Metropolitan Transportation, Beijing University of Technology, Beijing, 100124, China
  • [ 8 ] [Li, W.]Beijing Key Laboratory of Transportation Engineering, Beijing, 100124, China
  • [ 9 ] [Li, W.]Beijing Collaborative Innovation Center for Metropolitan Transportation, Beijing, 100124, China
  • [ 10 ] [Zhang, C.]College of Metropolitan Transportation, Beijing University of Technology, Beijing, 100124, China
  • [ 11 ] [Zhang, C.]Beijing Key Laboratory of Transportation Engineering, Beijing, 100124, China
  • [ 12 ] [Zhang, C.]Beijing Collaborative Innovation Center for Metropolitan Transportation, Beijing, 100124, China

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来源 :

Journal of Beijing University of Technology

ISSN: 0254-0037

年份: 2018

期: 6

卷: 44

页码: 910-918

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