Integrated Optimization of Bus Bridging Route Design and Bus Resource Allocation in Response to Metro Service Disruptions
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 148, Issue 8
Abstract
This paper focuses on the bus bridging service design in response to an unplanned metro line segment disruption. An integrated optimization model is constructed to address both bus bridging route layouts and bus resource allocation. Diversified routes, e.g., stop-by-stop route, express route, skip-stop route, parallel to the disrupted line segment are applied in the optimized bridging scheme to best respond to the passenger demands. An event-driven simulation-based genetic algorithm is designed to solve the optimization model. The simulation method is introduced to handle the uncertainty of passenger waiting time and the randomness of bus dwelling times at bridging stations and control the bus station capacities and guarantee the feasibility of the bridging schemes. Finally, the effectiveness of our proposed approaches is verified in a case study. Sensitivity analyses explore the impacts of fleet size and route diversity on the bridging performance. The results are instructive for transit agencies to operate bus bridging services.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This research was funded by the Natural Science Foundation of Zhejiang Province (Nos. LY21E080008 and LGF20E080010), Natural Science Foundation of Ningbo (No. 202003N4146), Shanghai Key Laboratory of Rail Infrastructure Durability and System Safety (No. R202002), and National Natural Science Foundation of China (No. 51408323). The authors want to thank anonymous reviewers for their insightful comments on this paper.
References
Andersson, E. V., A. Peterson, and J. T. Krasemann. 2013. “Quantifying railway timetable robustness in critical points.” J. Rail Transp. Plann. Manage. 3 (3): 95–110. https://doi.org/10.1016/j.jrtpm.2013.12.002.
Berche, B., C. Ferber, T. Holovatch, and Y. Holovatch. 2009. “Resilience of public transport networks against attacks.” Eur. Phys. J. B 71 (3): 125–137. https://doi.org/10.1140/epjb/e2009-00291-3.
Burggraeve, S., S. H. Bull, P. Vansteenwegen, and R. Lusby. 2017. “Integrating robust timetabling in line plan optimization for railway systems.” Transp. Res. Part C 77 (Jan): 134–160. https://doi.org/10.1016/j.trc.2017.01.015.
Cadarso, L., A. Marin, and G. Maroti. 2013. “Recovery of disruptions in rapid transit networks.” Transp. Res. Part E 53 (1): 15–33. https://doi.org/10.1016/j.tre.2013.01.013.
Currie, G., and C. Muir. 2017. “Understanding passenger perceptions and behaviors during unplanned rail disruptions.” Transp. Res. Procedia 25 (May): 4392–4402. https://doi.org/10.1016/j.trpro.2017.05.322.
Deng, Y. J., X. L. Ru, Z. Q. Dou, and G. H. Liang. 2018. “Design of bus bridging routes in response to disruption of urban rail transit.” Sustainability 10 (4427): 1–17. https://doi.org/10.3390/su10124427.
Fischetti, M., D. Salvagnin, and A. Zanette. 2009. “Fast approaches to improve the robustness of a railway timetable.” Transp. Sci. 43 (3): 321–335. https://doi.org/10.1287/trsc.1090.0264.
Gu, W., J. Yu, Y. X. Ji, Y. J. Zheng, and H. M. Zhang. 2018. “Plan-based flexible bus bridging operation strategy.” Transp. Res. Part C 91 (3): 209–229. https://doi.org/10.1016/j.trc.2018.03.015.
Hu, H., Y. F. Gao, J. Yu, Z. G. Liu, and X. Li. 2016. “Planning bus bridging evacuation during rail transit operation disruption.” J. Urban Plann. Dev. 142 (4): 04016015. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000335.
Jin, J. G., L. C. Tang, L. J. Sun, and D. H. Lee. 2014. “Enhancing metro network resilience via localized integration with bus services.” Transp. Res. Part E 63 (12): 17–30. https://doi.org/10.1016/j.tre.2014.01.002.
Jin, J. G., K. M. Teo, and A. R. Odoni. 2015. “Optimizing bus bridging services in response to disruptions of urban transit rail networks.” Transp. Sci. 50 (3): 790–804. https://doi.org/10.1287/trsc.2014.0577.
Karabuk, S., and H. Manzour. 2019. “A multi-stage stochastic program for evacuation management under tornado track uncertainty.” Transp. Res. Part E. 124: 128–151. https://doi.org/10.1016/j.tre.2019.02.005.
Kepaptsoglou, K., and M. G. Karlaftis. 2009. “The bus bridging problem in metro operations: Conceptual framework, models and algorithms.” Public Transp. 1 (13): 275–297. https://doi.org/10.1007/s12469-010-0017-6.
Liang, J. P., J. J. Wu, Y. C. Qu, H. D. Yin, X. B. Qu, and Z. Y. Gao. 2019. “Robust bus bridging service design under rail transit system disruptions.” Transp. Res. Part E 132 (Feb): 97–116. https://doi.org/10.1016/j.tre.2019.10.008.
Liu, L., and M. Dessouky. 2019. “Stochastic passenger train timetabling using a branch and bound approach.” Comput. Ind. Eng. 127 (Apr): 1223–1240. https://doi.org/10.1016/j.cie.2018.03.016.
Louie, J., A. Shalaby, and K. N. Habib. 2017. “Modelling the impact of causal and non-causal factors on disruption duration for Toronto’s subway system: An exploratory investigation using hazard modelling.” Accid. Anal. Prev. 98 (10): 232–240. https://doi.org/10.1016/j.aap.2016.10.008.
Luo, C. L., and L. Xu. 2021. “Railway disruption management: Designing bus bridging services under uncertainty.” Comput. Oper. Res. 131 (21): 105284. https://doi.org/10.1016/j.cor.2021.105284.
Malandri, C., A. Fonzone, and O. Cats. 2018. “Recovery time and propagation effects of passenger transport disruptions.” Physica A 505 (Mar): 7–17. https://doi.org/10.1016/j.physa.2018.03.028.
Pender, B., G. Currie, A. Delbosc, and N. Shiwakoti. 2013. “Disruption recovery in passenger railways: International survey.” Transp. Res. Rec. J. Transp. Res. Board 2353 (1): 22–32. https://doi.org/10.3141/2353-03.
Qu, H. Z., R. J. Li, and S. Chien. 2021. “Maximizing ridership through integrated bus service considering travel demand elasticity with genetic algorithm.” J. Transp. Eng. Part A: Syst. 147 (4): 04021010. https://doi.org/10.1061/JTEPBS.0000511.
Schöbel, A., and A. Krat. 2009. “A bicriteria approach for robust timetabling.” In Robust and online large-scale optimization. Berlin: Springer.
Sun, H. J., J. J. Wu, L. J. Wu, X. Y. Yan, and Z. Y. Gao. 2016. “Estimating the influence of common disruptions on urban rail transit networks.” Transp. Res. Part A 94 (6): 62–75. https://doi.org/10.1016/j.tra.2016.09.006.
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.” Transp. Res. Part A 108 (Dec): 12–24. https://doi.org/10.1016/j.tra.2017.12.008.
Tan, Z. J., M. Xu, Q. Meng, and Z. C. Li. 2020. “Evacuating metro passengers via the urban bus system under uncertain disruption recovery time and heterogeneous risk-taking behavior.” Transp. Res. Part C 119 (15): 102761. https://doi.org/10.1016/j.trc.2020.102761.
Wang, Y., X. D. Yan, Y. Zhou, and W. Y. Zhang. 2016. “A feeder-bus dispatch planning model for emergency evacuation in urban rail transit corridors.” PLoS One 11 (9): 1–28. https://doi.org/10.1371/journal.pone.0161644.
Yin, H. D., B. M. Han, D. W. Li, and Y. Wang. 2016. “Evaluating disruption in rail transit network: A case study of Beijing subway.” Procedia Eng. 137 (5): 49–58. https://doi.org/10.1016/j.proeng.2016.01.233.
Yin, H. D., J. J. Wu, H. J. Sun, Y. C. Qu, X. Yang, and B. Wang. 2018. “Optimal bus-bridging service under a metro station disruption.” J. Adv. Transp. 2018 (Jan): 1–16. https://doi.org/10.1155/2018/2758652.
Zeng, A. Z., C. F. Durach, and Y. Fang. 2012. “Collaboration decisions on disruption recovery service in urban public tram systems.” Transp. Res. Part E 48 (11): 578–590. https://doi.org/10.1016/j.tre.2011.11.005.
Zhang, S. Y., and H. K. Lo. 2018. “Metro disruption management: Optimal initiation time of substitute bus services under uncertain system recovery time.” Transp. Res. Part C 97 (Nov): 409–427. https://doi.org/10.1016/j.trc.2018.11.001.
Zhang, S. Y., and H. K. Lo. 2020. “Metro disruption management: Contracting substitute bus service under uncertain system recovery time.” Transp. Res. Part C 110 (Jan): 98–122. https://doi.org/10.1016/j.trc.2019.11.010.
Information & Authors
Information
Published In
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Jul 28, 2021
Accepted: Mar 7, 2022
Published online: May 31, 2022
Published in print: Aug 1, 2022
Discussion open until: Oct 31, 2022
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.
Cited by
- Shiyang Sun, Xin Guo, Huijun Sun, Optimization of Bus Bridging Strategy for Two Bus Types during Planned Metro Disruptions, Journal of Transportation Engineering, Part A: Systems, 10.1061/JTEPBS.TEENG-8482, 150, 11, (2024).
- Jiefei Zhang, Gang Ren, Jianhua Song, Resilience-based optimization model for emergency bus bridging and dispatching in response to metro operational disruptions, PLOS ONE, 10.1371/journal.pone.0277577, 18, 3, (e0277577), (2023).
- Hamed Jafari Kaleybar, Mohsen Davoodi, Morris Brenna, Dario Zaninelli, Applications of Genetic Algorithm and Its Variants in Rail Vehicle Systems: A Bibliometric Analysis and Comprehensive Review, IEEE Access, 10.1109/ACCESS.2023.3292790, 11, (68972-68993), (2023).