Bayesian Analysis for Metro Passenger Flows Using Automated Data

Chunya Li; Shifeng Xiong; Xuan SunYong QinXianyi Wu

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Bayesian Analysis for Metro Passenger Flows Using Automated Data

机译：Bayesian Analysis for Metro Passenger Flows Using Automated Data

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With the fast development of metro systems in many big cities, it is important to study the characteristics of passenger flows based on metro data for the management to guarantee service quality and safety. In this article, we build statistical models for the data of passengers’ tap-in and tap-out times in both no-transfer and one-transfer cases, and propose a Bayesian approach to estimate parameters in the models. These estimators can be used to evaluate a number of measures, which describe degrees of congestion and comfort, and to quantify their uncertainties. Application of our approach to Beijing metro shows different passengers follow different patterns between different routes and between off-peak and peak hours.

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来源
《Mathematical Problems in Engineering: Theory, Methods and Applications》 |2022年第8期|1.1-1.12|共12页
作者
Chunya Li; Shifeng Xiong; Xuan SunYong QinXianyi Wu;
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NCMIS, KLSC Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190;

School of Traffic and Transportation Beijing Jiaotong University Beijing 100044;

State Key Lab of Rail Traffic Control and Safety Beijing Jiaotong University Beijing 100044School of Mathematics Physics and Statistics Shanghai University of Engineering Science Shanghai 201620;

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Bayesian Analysis for Metro Passenger Flows Using Automated Data

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