Unveiling the evolution of urban rail transit network: considering ridership attributes

References

• Awad, F. A., D. J. Graham, L. AitBihiOuali, and R. Singh. 2023. “Performance of Urban Rail Transit: A Review of Measures and Interdependencies.” Transport Reviews 43 (4): 698–725. https://doi.org/10.1080/01441647.2023.2166146.
   Web of Science ®Google Scholar
• Cats, O. 2017. “Topological Evolution of a Metropolitan Rail Transport Network: The Case of Stockholm.” Journal of Transport Geography 62:172–183. https://doi.org/10.1016/j.jtrangeo.2017.06.002.
   Web of Science ®Google Scholar
• Chen, H. Y., B. Chen, L. M. Zhang, and H. X. Li. 2021. “Vulnerability Modeling, Assessment, and Improvement in Urban Metro Systems: A Probabilistic System Dynamics Approach.” Sustainable Cities and Society 75:103329. https://doi.org/10.1016/j.scs.2021.103329.
   Web of Science ®Google Scholar
• Cheng, Y., X. F. Ye, and T. Fujiyama. 2022. “How Does Interchange Affect passengers’ Route Choices in Urban Rail Transit? – A Case Study of the Shanghai Metro.” Transportation Letters 14 (4): 416–426. https://doi.org/10.1080/19427867.2021.1883803.
   Web of Science ®Google Scholar
• Chen, Z., Q. He, X. Su, Y. Yuan, and S. Chen. 2021. “The Opening Conditions of the Metro and Its Early Characteristics: A Historical Perspective.” Tunnelling and Underground Space Technology 108:103732. https://doi.org/10.1016/j.tust.2020.103732.
   Web of Science ®Google Scholar
• Chen, H. Y., Q. P. Shen, and Z. B. Feng. 2023. “Vulnerability Assessment in Urban Metro Systems Based on an Improved Cloud Model and a Bayesian Network.” Sustainable Cities and Society 98:104823. https://doi.org/10.1016/j.scs.2023.104823.
   Web of Science ®Google Scholar
• Deng, K., and L. Li. 2023. “Rail Transit and the Growth of Consumer Amenities: Evidence from Chinese Cities.” Transportation 24. https://doi.org/10.1007/s11116-023-10379-z.
   Google Scholar
• Deng, Y. X., S. Y. Liu, and D. Zhou. 2023. “Dependency Cluster Analysis of Urban Road Network Based on Percolation.” Transportation Research Part C: Emerging Technologies 154:154. https://doi.org/10.1016/j.trc.2023.104264.
   Web of Science ®Google Scholar
• Ding, R., N. Ujang, H. Hamid, J. J. Wu, and W.-B. Du. 2015. “Complex Network Theory Applied to the Growth of Kuala Lumpur’s Public Urban Rail Transit Network.” PLOS ONE 10 (10): e0139961. https://doi.org/10.1371/journal.pone.0139961.
   PubMed Web of Science ®Google Scholar
• Freeman, L. C. 1977. “A Set of Measures of Centrality Based Upon Betweenness.” Sociometry 40 (1): 35–41. https://doi.org/10.2307/3033543.
   Google Scholar
• He, Y. X., Y. Zhao, and K. L. Tsui. 2020. “Modeling and Analyzing Modeling and Analyzing Impact Factors of Metro Station Ridership: An Approach Based on a General Estimating Equation Factors Influencing Metro Station Ridership: An Approach Based on General Estimating Equation.” IEEE Intelligent Transportation Systems Magazine 12 (4): 195–207. https://doi.org/10.1109/MITS.2020.3014438.
   Web of Science ®Google Scholar
• Huang, W. C., H. R. Li, Y. H. Yin, Z. Zhang, A. H. Xie, Y. Zhang, and G. Chen. 2024. “Node Importance Identification of Unweighted Urban Rail Transit Network: An Adjacency Information Entropy Based Approach.” Reliability Engineering and System Safety 242:109766. https://doi.org/10.1016/j.ress.2023.109766.
   Web of Science ®Google Scholar
• Ingvardson, J. B., and O. A. Nielsen. 2018. “How Urban Density, Network Topology and Socio-Economy Influence Public Transport Ridership: Empirical Evidence from 48 European Metropolitan Areas.” Journal of Transport Geography 72:50–63. https://doi.org/10.1016/j.jtrangeo.2018.07.002.
   Web of Science ®Google Scholar
• Kohonen, T. 2013. “Essentials of the Self-Organizing Map.” Neural Networks 37:52–65. https://doi.org/10.1016/j.neunet.2012.09.018.
   PubMed Web of Science ®Google Scholar
• Latora, V., and M. Marchiori. 2002. “Is the Boston Subway a Small-World Network?” Physica A: Statistical Mechanics and Its Applications 314 (1–4): 109–113. https://doi.org/10.1016/S0378-4371(02)01089-0.
   Web of Science ®Google Scholar
• Li, G. H., F. Liu, and H. Yang. 2022. “Research on Feature Extraction Method of Ship Radiated Noise with K-Nearest Neighbor Mutual Information Variational Mode Decomposition, Neural Network Estimation Time Entropy and Self-Organizing Map Neural Network.” Measurement 199:111446. https://doi.org/10.1016/j.measurement.2022.111446.
   Web of Science ®Google Scholar
• Liu, X. L., C. X. Jiang, F. Wang, and S. J. Yao. 2021. “The Impact of High-Speed Railway on Urban Housing Prices in China: A Network Accessibility Perspective.” Transportation Research Part A: Policy and Practice 152:84–99. https://doi.org/10.1016/j.tra.2021.08.006.
   Web of Science ®Google Scholar
• Liu, S., E. Yao, and B. Li. 2019. “Exploring Urban Rail Transit Station-Level Ridership Growth with Network Expansion.” Transportation Research Part D: Transport & Environment 73:391–402. https://doi.org/10.1016/j.trd.2018.04.006.
   Web of Science ®Google Scholar
• Li, M., Y. H. Wang, L. M. Jia, and Y. R. Cui. 2020. “Risk Propagation Analysis of Urban Rail Transit Based on Network Model.” Alexandria Engineering Journal 59 (3): 1319–1331. https://doi.org/10.1016/j.aej.2020.02.030.
   Web of Science ®Google Scholar
• Ma, M., D. W. Hu, S. I. J. Chien, J. Liu, X. Yang, and Z. L. Ma. 2022. “Evolution Assessment of Urban Rail Transit Networks: A Case Study of Xi’an, China.” Physica A: Statistical Mechanics and Its Applications 603:127670. https://doi.org/10.1016/j.physa.2022.127670.
   Web of Science ®Google Scholar
• Ma, Z. A., X. Yang, J. J. Wu, A. Chen, Y. Wei, and Z. Y. Gao. 2022. “Measuring the Resilience of an Urban Rail Transit Network: A Multi-Dimensional Evaluation Model.” Transport Policy 129:38–50. https://doi.org/10.1016/j.tranpol.2022.10.003.
   Web of Science ®Google Scholar
• Mohammadi, A., L. Amador-Jimenez, and F. Nasiri. 2019. “Review of Asset Management for Metro Systems: Challenges and Opportunities.” Transport Reviews 39 (3): 309–326. https://doi.org/10.1080/01441647.2018.1470119.
   Web of Science ®Google Scholar
• Peng, J. D., C. W. Cui, J. J. Qi, Z. H. Ruan, Q. Dai, and H. Yang. 2021. “The Evolvement of Rail Transit Network Structure and Impact on Travel Characteristics: A Case Study of Wuhan.” ISPRS International Journal of Geo-Information 10 (11): 789. https://doi.org/10.3390/ijgi10110789.
   Web of Science ®Google Scholar
• Shanmukhappa, T., I. W. Ho, C. Tse, and K. K. Leung. 2019. “Recent Development in Public Transport Network Analysis from the Complex Network Perspective.” IEEE Circuits and Systems Magazine 19 (4): 39–65. https://doi.org/10.1109/MCAS.2019.2945211.
   Web of Science ®Google Scholar
• Shen, Y., H. Yang, G. Ren, and B. Ran. 2023. “Model Cascading Overload Failure and Dynamic Vulnerability Analysis of Facility Network of Metro Station.” Reliability Engineering & System Safety 242:109711. https://doi.org/10.1016/j.ress.2023.109711.
   Web of Science ®Google Scholar
• Sun, L. S., Y. C. Huang, Y. Y. Chen, and L. Y. Yao. 2018. “Vulnerability Assessment of Urban Rail Transit Based on Multi-Static Weighted Method in Beijing, China.” Transportation Research Part A: Policy and Practice 108:12–24. https://doi.org/10.1016/j.tra.2017.12.008.
   Web of Science ®Google Scholar
• Wang, Y. Q., X. B. Cao, F. Y. Qin, and L. Tong. 2022. “Vulnerability Analysis of the Chinese Coupled Aviation and High-Speed Railway Network.” Chinese Journal of Aeronautics 35 (12): 189–199. https://doi.org/10.1016/j.cja.2022.01.009.
   Web of Science ®Google Scholar
• Wang, X. F., M. Othman, D. A. Dewi, and Y. H. Wang. 2024. “WSLC: Weighted Semi-Local Centrality to Identify Influential Nodes in Complex Networks.” Journal of King Saud University - Computer and Information Sciences 36 (1): 101906. https://doi.org/10.1016/j.jksuci.2023.101906.
   Web of Science ®Google Scholar
• Wang, Z. R., G. F. Su, and Z. L. Liang. 2016. “Information Transfer Efficiency Based Small-World Assessment Methodology for Metro Networks.” Journal of Tsinghua University (Science and Technology) 56 (4): 411–416. https://doi.org/10.16511/j.cnki.qhdxxb.2016.24.012.
   Google Scholar
• Wang, X., Q. Wang, and S. Liang. 2020. “Predictive Control Algorithm for Urban Rail Train Brake Control System Based on T-S Fuzzy Model.” Computers Materials & Continua 64 (3): 1859–1867. https://doi.org/10.32604/cmc.2020.011032.
   Web of Science ®Google Scholar
• Xin, M., and S. Feng. 2024. “Urban Rail Transit Network Topology Evolutionary Stage Has Influence on Rail Ridership: Insights from Linear Mixed-Effects Models with Heterogeneity in Variances.” Transportation Research Part A: Policy and Practice 180:103951. https://doi.org/10.1016/j.tra.2023.103951.
   Web of Science ®Google Scholar
• Xin, Z. L., and F. Q. Niu. 2023. “Structure and Robustness of China’s Railway Transport Network.” Transportation Letters 15 (5): 375–385. https://doi.org/10.1080/19427867.2022.2053280.
   Web of Science ®Google Scholar
• Xin, M. W., and A. Shalaby. 2024. “Investigation of the Interaction Between Urban Rail Ridership and Network Topology Characteristics Using Temporal Lagged and Reciprocal Effects: A Case Study of Chengdu, China.” Transportation Research Part A: Policy and Practice 179:103922. https://doi.org/10.1016/j.tra.2023.103922.
   Web of Science ®Google Scholar
• Yang, Z. J., and X. L. Chen. 2018. “Evolution Assessment of Shanghai Urban Rail Transit Network.” Physica A: Statistical Mechanics and its Applications 503:1263–1274. https://doi.org/10.1016/j.physa.2018.08.099.
   Web of Science ®Google Scholar
• Yang, H., C. Huang, Y. Huang, and Y. S. Pai. 2014. “A Weather-Based Hybrid Method for 1-Day Ahead Hourly Forecasting of PV Power Output.” IEEE Transactions on Sustainable Energy 5 (3): 917–926. https://doi.org/10.1109/TSTE.2014.2313600.
   Web of Science ®Google Scholar
• Yin, D. Z., W. C. Huang, B. Shuai, H. Y. Liu, and Y. Zhang. 2022. “Structural Characteristics Analysis and Cascading Failure Impact Analysis of Urban Rail Transit Network: From the Perspective of Multi-Layer Network.” Reliability Engineering and System Safety 218 (PA): 108161. https://doi.org/10.1016/j.ress.2021.108161.
   Google Scholar
• Yu, X. Y., Z. Chen, F. Liu, and H. H. Zhu. 2023. “How Urban Metro Networks Grow: From a Complex Network Perspective.” Tunnelling and Underground Space Technology 131:104841. https://doi.org/10.1016/j.tust.2022.104841.
   Web of Science ®Google Scholar
• Yue, Y., J. Han, S. Wang, and X. Liu. 2017. “Integrated Train Timetabling and Rolling Stock Scheduling Model Based on Time‐Dependent Demand for Urban Rail Transit.” Computer‐Aided Civil and Infrastructure Engineering 32 (10): 856–873. https://doi.org/10.1111/mice.12300.
   Web of Science ®Google Scholar
• Zhang, J. Agent-Based Optimizing Match Between Passenger Demand and Service Supply for Urban Rail Transit Network with Net Logo. IEEE Access, 2021. https://doi.org/10.1109/ACCESS.2021.3060816.
   Google Scholar
• Zhang, D., F. Du, H. Huang, F. Zhang, B. M. Ayyub, and M. Beer. 2018. “Resiliency Assessment of Urban Rail Transit Networks: Shanghai Metro as an Example.” Safety Science 106:230–243. https://doi.org/10.1016/j.ssci.2018.03.023.
   Web of Science ®Google Scholar
• Zhang, J., Z. Wang, S. Wang, Y. Y. Luan, and W. C. Shao. 2020. “Vulnerability Assessments of Urban Rail Transit Networks Based on Redundant Recovery.” Sustainability 12 (14): 5756. https://doi.org/10.3390/su12145756.
   Web of Science ®Google Scholar
• Zhang, L., H. Y. Wen, J. Lu, D. Lei, S. L. Li, and S. V. Ukkusuri. 2022. “Exploring Cascading Reliability of Multi-Modal Public Transit Network Based on Complex Networks.” Reliability Engineering and System Safety 201:108367. https://doi.org/10.1016/j.ress.2022.108367.
   Google Scholar