Abstract
As modern large cities heavily rely on urban rail transit (URT) systems as their most crucial transportation infrastructure to meet daily commuting demands, the irrational design of the first train timetable and the lack of effective connections between different lines could result in excessively long travel times for passengers. Therefore, it is necessary to explore the flow organization mechanism of the URT system. In this paper, based on the temporal network theory, the concept of the First-Train-Timetable-Network (FTTN) is proposed, and the FTTN organization mechanism of Beijing and Shanghai’s URT systems is studied based on the percolation theory. We discovered an important parameter that can characterize the rationality of the first train timetable arrangement, namely, the critical time \({\text{t}}_{\text{c}}\). Additionally, we observed the FTTN’s percolation transition phenomenon and evaluated the network performance. The results show that the FTTN model proposed in this study, together with the URT network performance evaluation method, can effectively reflect the actual situation of the URT network, providing valuable insights for URT operators to formulate the first train timetable.
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References
Ma, Z., Yang, X., Wu, J., Chen, A., Wei, Y., Gao, Z.: Measuring the resilience of an urban rail transit network: A multi-dimensional evaluation model. Transp. Policy 129, 38–50 (2022)
Du, Y., Wang, H., Gao, Q., Pan, N., Zhao, C., Liu, C.: Resilience concepts in integrated urban transport: a comprehensive review on multi-mode framework. SRT 4, 105–133 (2022)
Guo, H., Bai, Y., Hu, Q., Zhuang, H., Feng, X.: Optimization on metro timetable considering train capacity and passenger demand from intercity railways. SRT 3, 66–77 (2021)
Eckmann, J.-P., Moses, E., Sergi, D.: Entropy of dialogues creates coherent structures in e-mail traffic. Proc. Natl. Acad. Sci. U.S.A. 101, 14333–14337 (2004)
Adar, E., Adamic, L.A.: Tracking information epidemics in Blogspace. In: The 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI’05), pp. 207–214. IEEE, Compiegne, France (2005)
Han, J.-D.J., et al.: Evidence for dynamically organized modularity in the yeast protein–protein interaction network. Nature 430, 88–93 (2004)
Wang, F., Li, D., Xu, X., Wu, R., Havlin, S.: Percolation properties in a traffic model. EPL 112, 38001 (2015)
Li, D., et al.: Percolation transition in dynamical traffic network with evolving critical bottlenecks. Proc. Natl. Acad. Sci. U.S.A. 112, 669–672 (2015)
Zeng, G., et al.: Switch between critical percolation modes in city traffic dynamics. Proc. Natl. Acad. Sci. U.S.A. 116, 23–28 (2019)
Zeng, G., et al.: Multiple metastable network states in urban traffic. Proc. Natl. Acad. Sci. U.S.A. 117, 17528–17534 (2020)
Schneider, C.M., Moreira, A.A., Andrade, J.S., Havlin, S., Herrmann, H.J.: Mitigation of malicious attacks on networks. Proc. Natl. Acad. Sci. U.S.A. 108, 3838–3841 (2011)
Tang, J., Musolesi, M., Mascolo, C., Latora, V.: Temporal distance metrics for social network analysis. In: Proceedings of the 2nd ACM Workshop on Online Social Networks, pp. 31–36. ACM, Barcelona Spain (2009)
Nicosia, V., Tang, J., Musolesi, M., Russo, G., Mascolo, C., Latora, V.: Components in time-varying graphs. Chaos 22, 023101 (2012)
Acknowledgement
This research was supported by the National Key R&D Program of China (No. 2020YFB1600702), the National Natural Science Foundation of China (Nos. 72071015, 72288101).
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Zhu, T., Ma, Z., Yang, X. (2024). Evaluating First-Train-Timetable-Network Performance in Urban Rail Transit with Percolation Theory. In: Qin, Y., Jia, L., Yang, J., Diao, L., Yao, D., An, M. (eds) Proceedings of the 6th International Conference on Electrical Engineering and Information Technologies for Rail Transportation (EITRT) 2023. EITRT 2023. Lecture Notes in Electrical Engineering, vol 1137. Springer, Singapore. https://doi.org/10.1007/978-981-99-9311-6_5
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DOI: https://doi.org/10.1007/978-981-99-9311-6_5
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