Research on the Impact of Urban Rail Transit Network Topology on Transfer Convenience: Evidence from 50 Cities Worldwide

Previous research on urban rail transit (URT) transfer convenience mainly focused on the transfer stations, often neglecting the impact of network topology. This paper uses the transfer convenience index to characterize the transfer convenience and extracts the topological indicators, including the collinearity degree, from the URT networks of fifty global cities. Leveraging a back propagation neural network model integrated with SHAP, the study analyzes the transfer convenience and influencing factors of the URT network. Our findings reveal a threshold effect of the collinearity degree on transfer convenience. When the collinearity degree is disregarded, the relationship between the transfer convenience index and the number of transfer stations predominantly aligns with an exponential function model. When the transfer station number exceeds 15, the transfer convenience index reaches its maximum in a ring–radial morphology. The conclusion could help urban planners understand the changing rules of transfer convenience in the URT network, guiding strategic decisions on transfer station placement and network morphology selection.

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Publication Details

Journal
Sustainability
Published
2025-11-04
DOI
https://doi.org/10.3390/su17219821
Primary Topic
Transportation Planning and Optimization
Type
article
Field-Weighted Citation Impact
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Research on the Impact of Urban Rail Transit Network Topology on Transfer Convenience: Evidence from 50 Cities Worldwide

Yunpeng Zhao, Wen Xiong, Xuhui Zhang, Qing Li et al.
Sustainability
Transportation Planning and Optimization
article

Research on the Impact of Urban Rail Transit Network Topology on Transfer Convenience: Evidence from 50 Cities Worldwide

Yunpeng Zhao, Wen Xiong, Xuhui Zhang, Qing Li, Zhenjun Zhu, Xinyu Hu
article en

Abstract

Previous research on urban rail transit (URT) transfer convenience mainly focused on the transfer stations, often neglecting the impact of network topology. This paper uses the transfer convenience index to characterize the transfer convenience and extracts the topological indicators, including the collinearity degree, from the URT networks of fifty global cities. Leveraging a back propagation neural network model integrated with SHAP, the study analyzes the transfer convenience and influencing factors of the URT network. Our findings reveal a threshold effect of the collinearity degree on transfer convenience. When the collinearity degree is disregarded, the relationship between the transfer convenience index and the number of transfer stations predominantly aligns with an exponential function model. When the transfer station number exceeds 15, the transfer convenience index reaches its maximum in a ring–radial morphology. The conclusion could help urban planners understand the changing rules of transfer convenience in the URT network, guiding strategic decisions on transfer station placement and network morphology selection.

SustainabilityVol. 17(21)
Nanjing Forestry University (CN), China Railway Group (China) (CN), Guangzhou Metro Group (China) (CN)
Openalex Percentile: Top 67%
Transportation Planning and Optimization
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