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Real-time origin-destination matrices estimation for urban rail transit network based on structural state-space model

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Abstract

The major objective of this work was to establish a structural state-space model to estimate the dynamic origin-destination (O-D) matrices for urban rail transit network, using in- and out-flows at each station from automatic fare collection (AFC) system as the real time observed passenger flow counts. For lacking of measurable passenger flow information, the proposed model employs priori O-D matrices and travel time distribution from historical travel records in AFC system to establish the dynamic system equations. An arriving rate based on travel time distribution is defined to identify the dynamic interrelations between time-varying O-D flows and observed flows, which greatly decreases the computational complexity and improve the model’s applicability for large-scale network. This methodology is tested in a real transit network from Beijing subway network in China through comparing the predicted matrices with the true matrices. Case study results indicate that the proposed model is effective and applicative for estimating dynamic O-D matrices for large-scale rail transit network.

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Authors and Affiliations

  1. School of Traffic and Transportation, Beijing Jiaotong University, Beijing, 100044, China

    Xiang-ming Yao  (姚向明), Peng Zhao  (赵鹏) & Dan-dan Yu  (禹丹丹)

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  1. Xiang-ming Yao  (姚向明)
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  2. Peng Zhao  (赵鹏)
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  3. Dan-dan Yu  (禹丹丹)
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Corresponding author

Correspondence to Peng Zhao  (赵鹏).

Additional information

Foundation item: Project(51478036) supported by the National Natural Science Foundation of China; Project(20120009110016) supported by Research Fund for Doctoral Program of Higher Education, China

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Yao, Xm., Zhao, P. & Yu, Dd. Real-time origin-destination matrices estimation for urban rail transit network based on structural state-space model. J. Cent. South Univ. 22, 4498–4506 (2015). https://doi.org/10.1007/s11771-015-2998-4

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  • DOI: https://doi.org/10.1007/s11771-015-2998-4

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