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Understanding Route Choice Behavior in Composite Urban Rail Transit Network with Interpretable Machine-Learning Approach: A Case Study in Shanghai, China

Crossref DOI link: https://doi.org/10.1007/s40864-025-00266-4

Published Online: 2026-02-20

Published Print: 2026-03

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Zhao, Qianwei

Chen, Enhui

Teng, Jing

Wu, Tong
Funding

Funding for this research was provided by:

National Natural Science Foundation of China (52402388)

Fundamental Research Funds for the Central Universities
License Information

Text and Data Mining valid from 2026-02-20

Version of Record valid from 2026-02-20
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Article History

Received: 15 August 2025

Revised: 9 November 2025

Accepted: 20 December 2025

First Online: 20 February 2026

Declarations

:

: All the authors have no conflict of interest with the funding entity and any organization mentioned in this article in the past three years that may have influenced the conduct of this research and the findings.

: All the authors have contributed to the work described, read and approved the contents for publication in this journal

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