Unveiling the evolution of urban rail transit network: considering ridership attributes
Document Type
Journal Article
Publication Date
2025
Subject Area
place - asia, place - urban, mode - rail, planning - network design, planning - methods, ridership - growth
Keywords
Urban rail transit, network evolution, ridership attributes, complex network theory, network topology index, self-organizing mapping neural networks
Abstract
Previous research on urban rail transit (URT) evolution mainly focused on network topology, neglecting ridership attributes. This study extracts ridership and network topology indicators from Chinese URT data. Employing a self-organizing mapping neural network model, it divides China’s URT development into four stages. The initial stage and the development stage form the framework of URT network. The network diameter reaches the maximum in the networked operation stage. In the mature stage, URT network densification occurs alongside a significant increase in resident ridership. It is also found that each network indicator has a significant nonlinear relationship with ridership attributes. These findings are of guiding significance for urban planners to accurately understanding URT’s future development and rational network planning and construction.
Rights
Permission to publish the abstract has been given by Taylor&Francis, copyright remains with them.
Recommended Citation
Zhao, Y., Zhu, Z., Zhang, Y., Yang, Y., Guo, Y., & Zhou, W. (2025). Unveiling the evolution of urban rail transit network: considering ridership attributes. Transportation Letters, 17(2), 310-321.
