Evaluating Service Risk in Railway Capacity Utilization Using Expected Recovery Time
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 143, Issue 6
Abstract
Different capacity-utilization levels may incur different service risks to the railway system. Previous capacity research has mainly focused on capacity measurement without evaluating the potential risks from an increase in the capacity-utilization level. This research proposes a new concept, namely, risk in capacity utilization, by using expected recovery time to quantify the service risk in capacity utilization. A corresponding computational process was also developed to assess the expected time for the railway operation to recover after potential disruptions. Results from the case study demonstrate that the service risk in capacity utilization can be obtained and compared by using the proposed concept and process. A minor increase in the capacity-utilization level in peak hours may incur a substantial risk to service reliability. In order to adjust the service plan to a desired reliability level, the locations and time intervals causing a high level of capacity risk can also be pinpointed in the risk-evaluation process. It is therefore important and beneficial to incorporate this evaluation procedure in the service-design process to ensure service reliability to customers.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
This project was funded by the Ministry of Science and Technology of Taiwan under 103-2221-E-002-130-MY3.
References
Abril, M., Barber, F., Ingolotti, L., and Salido, M. (2008). “An assessment of railway capacity.” Transp. Res. Part E: Logist. Transp. Rev., 44(5), 774–806.
Carey, M. (1998). “Optimizing scheduled times, allowing for behavioural response.” Transp. Res. Part B: Methodol., 32(5), 329–342.
Carey, M., and Carville, S. (2000). “Testing schedule performance and reliability for train stations.” J. Oper. Res. Soc., 51(6), 666–682.
Cicerone, S., D’Angelo, G., Di Stegano, G., Frigioni, D., and Navarra, A. (2009). “Recoverable robust timetabling for single delay: Complexity and polynomial algorithms for special cases.” J. Comb. Optim., 18(3), 229–257.
Delorme, X., Gandibleux, X., and Rodriguez, J. (2009). “Stability evaluation of a railway timetable at station level.” Eur. J. Oper. Res., 195(3), 780–790.
Engelhardt-Funke, O., and Kolonko, M. (2004). “Analysing stability and investments in railway networks using advanced evolutionary algorithms.” Int. Transp. Oper. Res., 11(4), 381–394.
Goverde, R. M. P. (2007). “Railway timetable stability analysis using max-plus system theory.” Transp. Res. Part B: Methodol., 41(2), 179–201.
Higgins, A., Ferreira, L., and Kozan, E. (1995). “Modeling delay risks associated with train schedules.” Transp. Plan. Technol., 19(2), 89–108.
Higgins, A., and Kozan, E. (1998). “Modeling train delays in urban networks.” Transp. Sci., 32(4), 346–357.
Huisman, T., Boucherie, R. J., and Van Dijk, N. M. (2002). “A solvable queuing network model for railway networks and its validation and application for Netherlands.” Eur. J. Oper. Res., 142(1), 30–51.
Jong, J. C., Chang, E. F., and Huang, S. S. (2009). “A railway capacity for estimating hourly throughputs.” Proc., 3rd Int. Association of Railway Operations Research Conf., International Association of Railway Operations Research, Delft, Netherlands.
Jong, J. C., Lai, Y. C., Huang, S. H., and Chiang, P. C. (2011). “Development and application of rail transit capacity models in Taiwan.” Transp. Res. Rec., 2216, 125–138.
Kang, L., Wu, J., and Sun, H. (2012). “Using simulated annealing in a bottleneck optimization model at railway stations.” J. Transp. Eng., 1396–1402.
Kieu, L. M., Bhaskar, A., and Chung, E. (2015). “Public transport travel-time variability definitions and monitoring.” J. Transp. Eng., .
Lai, Y. C., Shih, M. C., and Jong, J. C. (2010). “Railway capacity model and decision support process for strategic capacity planning.” Transp. Res. Rec., 2197, 19–28.
Lai, Y. C., and Wang, S. H. (2012). “Development of analytical capacity models for conventional railways with advanced signaling systems.” J. Transp. Eng., 961–974.
Landex, A. (2009). “Evaluation of railway networks with single track operation using the UIC 406 capacity method.” Netw. Spatial Econ., 9(1), 7–23.
Li, F., Gao, Z., Li, K., and Wang, D. Z. (2013). “Train routing model and algorithm combined with train scheduling.” J. Transp. Eng., 81–91.
Vromans, M. J., Dkker, R., and Kroon, L. G. (2006). “Reliability and heterogeneity of railway services.” Eur. J. Oper. Res., 172(2), 647–665.
Weng, J., Zheng, Y., Yan, X., and Meng, Q. (2014). “Development of a subway operation incident delay model using accelerated failure time approaches.” Accid. Anal. Prev., 73, 12–19.
Yuan, J., and Hansen, I. A. (2007). “Optimizing capacity utilization of stations by estimating knock-on train delays.” Transp. Res. Part B: Methodol., 41(2), 202–217.
Zhao, H., Zhang, C., Gao, Z., and Si, B. (2013). “Risk-based transit schedule design for a fixed route from the view of equity.” J. Transp. Eng., 1086–1094.
Information & Authors
Information
Published In
Journal of Transportation Engineering, Part A: Systems
Volume 143 • Issue 6 • June 2017
Copyright
©2017 American Society of Civil Engineers.
History
Received: Jul 6, 2016
Accepted: Nov 1, 2016
Published online: Feb 17, 2017
Published in print: Jun 1, 2017
Discussion open until: Jul 17, 2017
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.