Abstract
Identifying the importance of metro stations is crucial for enhancing the efficiency and safety of the urban rail transit system. This study proposes an integrated approach to evaluate the importance of metro stations based on jointly the static metro network topology and the dynamic real-time passenger flows. The static characteristics of metro stations are reflected through node degree and clustering coefficient of metro network topology based on the complex network theory. The dynamic characteristics of metro stations are assessed using the passenger flow time series, which were modeled using the autoregressive integrated moving average plus autoregressive conditional heteroscedasticity model (i.e., ARIMA+GARCH model). By combining the static and dynamic characteristics of metro stations, a comprehensive index is proposed to quantify the importance of metro stations. The integrated approach is tested using metro network and passenger flow data collected from Suzhou, China. The results indicate that compared with the topology analysis, the passenger flows could strengthen the importance of transfer stations and their neighboring stations. Especially for the loop lines that formed by the intersection of two or more lines within the network, the importance index of metro stations within these loop lines is inversely proportional to the number of stations in the loop. It indicates that as a metro network continues to expand with the addition of new lines and stations, this is a high likelihood of increased concentration of importance with the network. The concentration of importance in the metro network can be attributed to the emergence of highly connected loop lines that facilitate efficient movement of passengers.
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Acknowledgments
The authors would like to thank the Suzhou Rail Transit Group Co., Ltd for providing the necessary data. The authors hold all the responsibility for the analyses and views presented in this work. Neither the entire paper nor any part of its content has been published or has been accepted elsewhere. This work is supported by the High-level Talent Introduction Fund from Nanjing Institute of Technology under grant No.YKJ201995.
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Peng, P., Liu, Z., Guo, J. et al. Dynamic Metro Stations Importance Evaluation Based on Network Topology and Real-Time Passenger Flows. KSCE J Civ Eng 27, 4459–4471 (2023). https://doi.org/10.1007/s12205-023-0954-7
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DOI: https://doi.org/10.1007/s12205-023-0954-7