Dynamic Modeling for Metro Passenger Flows on Congested Transfer Routes

Weiyan Mu, Xin Wang, Chunya Li () and Shifeng Xiong
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Weiyan Mu: School of Science, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
Xin Wang: School of Science, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
Chunya Li: School of Mathematics, Physics, and Statistics, Shanghai University of Engineering Science, Shanghai 201620, China
Shifeng Xiong: NCMIS, KLSC, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China

Mathematics, 2023, vol. 11, issue 6, 1-20

Abstract: With the rapid development of urbanization, the metro becomes more and more important for people’s travel in big cities. To quantitatively describe metro passenger flows on congested transfer routes, this paper introduces a dynamic model based on automated data from the automatic fare collection (AFC) and automatic vehicle location (AVL) systems. An expectation maximization (EM) algorithm is proposed to compute the maximum likelihood estimates of unknown parameters in our model. Our model can yield a systematic analysis of one-transfer passenger flows on both population and individual aspects. Important characteristics, including transfer time, boarding probabilities, walking time, passenger-to-train assignment probabilities, and total travel time, can be inferred using only the AFC and AVL data. We provide a case study on the Beijing metro. Detailed analysis results based on our model are given. We also present a cross-validation method to validate our model with real data.

Keywords: automated data; EM algorithm; passenger assignment; peak hours; statistical inference; transfer time (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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