Previous Chapter: Recommended Changes to the TCQSM
Suggested Citation: "References." National Academies of Sciences, Engineering, and Medicine. 2026. Operating Margin and Recovery Factor Practices for Travel Time Estimation and Rail Scheduling. Washington, DC: The National Academies Press. doi: 10.17226/29463.

introduced in the newly added preceding subsection. Include a sentence clarifying that irregularities resulting from variations in train performance, one of the components of operating margins, can be mitigated by carefully selecting a realistic runtime allowance, which significantly influences the calculation of the operating margin.

  • Section 2, Rail Capacity Fundamentals: Add a sentence to the Reliability subsection to emphasize how establishing a reasonable time allowance can significantly enhance operational reliability.
  • Section 4, Train Operations: Add a subsection between Examples of North American Operating Margins and Estimating Operating Margins titled Examples of Runtime Allowance. This subsection should provide a summary of the results of this small research task, including actual current approaches adopted by U.S. transit agencies, and the relationship of runtime allowance to dwell times and operating margins.
  • Section 4, Train Operations: Edit the Estimating Operating Margins subsection to mention the relationship between runtime allowances and operating margins.
  • Section 5, Rail System Capacity Methodologies: Incorporate the concept of runtime allowance throughout the section where applicable. Doing so entails discussing its connection with determining operating margins, minimum headways, and minimum train separation.

REFERENCES

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Carey, M. 1999. Ex ante heuristic measures of schedule reliability. Transportation Research Part B: Methodological, Vol. 33, Issue 7, pp. 473–494. https://doi.org/10.1016/S0191-2615(99)00002-8.

Fischetti, M., D. Salvagnin, and A. Zanette. 2009. Fast approaches to improve the robustness of a railway timetable. Transportation Science, Vol. 43, Issue 3, pp. 267–406. https://doi.org/10.1287/trsc.1090.0264.

Hansen, I., and J. Pachl (eds.). 2014. Railway Timetabling & Operations: Analysis, Modelling, Optimisation, Simulation, Performance Evaluation. Eurail Press, Hamburg, Germany.

International Union of Railways (UIC). 2000. Leaflet 541-1 OR – Timetable Recovery Margins to Guarantee Timekeeping – Recovery Margins. UIC, Paris, France.

Jin, B., X. Feng, Q. Wang, X. Wang, and C. Liu. 2019. “Improving Timetable Robustness through Optimal Distribution of Runtime Supplement.” Proceedings, 2019 IEEE Intelligent Transportation Systems Conference, Auckland, New Zealand, October 27–30, 2019. https://doi.org/10.1109/ITSC.2019.8917477.

Khoshniyat, F., and A. Peterson. 2017. Improving train service reliability by applying an effective timetable robustness strategy. Journal of Intelligent Transportation Systems, Vol. 21, Issue 6, pp. 525–543. https://doi.org/10.1080/15472450.2017.1326114.

Kroon, L., R. Dekker, and M. J. C. M. Vromans. 2007. Cyclic railway timetabling: A stochastic optimization approach. In Geraets, F., L. Kroon, A. Schoebel, D. Wagner, and C.D. Zaroliagis (eds.), Algorithmic Methods for Railway Optimization. Lecture Notes in Computer Science, Vol. 4359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74247-0_2.

Lindfeldt, A. 2015. Railway Capacity Analysis – Methods for Simulation and Evaluation of Timetables, Delays and Infrastructure. PhD thesis. KTH Royal Institute of Technology, Stockholm, Sweden. http://kth.diva-portal.org/smash/get/diva2:850511/FULLTEXT01.pdf. Accessed July 3, 2024.

Medeossi, G. 2010. Capacity and Reliability on Railway Networks: A Simulative Approach. PhD thesis. University of Trieste, Italy. https://www.openstarts.units.it/bitstreams/4459c472-6596-4400-8e65-550e5ed9bcc5/download. Accessed July 3, 2024.

Network Rail. 2024. Timetable Planning Rules – National – Version 4.0. Section 1.13.4 Timing Allowances – definitions and usage. London, U.K.

Norwegian Railway Directorate. 2022. Jernbanedirektoratets standard for rutemodeller. Oslo. https://www.jernbanedirektoratet.no/metoder-og-standarder/dokumenter-for-det-trafikfaglige-arbeidet/. Accessed April 13, 2024.

Palmqvist, C. W., N. O. E. Olsson, and L. Hiselius. 2017a. Delays for passenger trains on a regional railway line in southern Sweden. International Journal of Transport Development and Integration, Vol. 1, Issue 3, pp. 421–431. https://doi.org/10.2495/TDI-V1-N3-421-431.

Palmqvist, C. W., N. O. E. Olsson, and L. Hiselius. 2017b. Some influencing factors for passenger train punctuality in Sweden. International Journal of Prognostics and Health Management, Vol. 8. https://doi.org/10.36001/ijphm.2017.v8i3.2649.

Palmqvist, C. W., N. O. E. Olsson, and L. W. Hiselius. 2018. The plannersʼ perspective on train timetable errors in Sweden. Journal of Advanced Transportation. https://doi.org/10.1155/2018/8502819.

Palmqvist, C. W., N. Tomii, and Y. Ochiai. 2020. Explaining dwell time delays with passenger counts for some commuter trains in Stockholm and Tokyo. Journal of Rail Transport Planning & Management, Vol. 14. https://doi.org/10.1016/j.jrtpm.2020.100189.

Restel, F., Ł. Wolniewicz, and M. Mikulčić. 2021. Method for designing robust and energy efficient railway schedules. Energies, Vol. 14, No. 24. https://doi.org/10.3390/en14248248.

Salido, M. A., F. Barber, and L. Ingolotti. 2012. Robustness for a single railway line: analytical and simulation methods. Expert Systems with Applications, Vol. 39, Issue 18, pp. 13305–13327. https://doi.org/10.1016/j.eswa.2012.05.071.

Schlechte, T., and R. Borndörfer. 2010. Balancing efficiency and robustness – a bi-criteria optimization approach to railway track allocation. In Ehrgott, M., B. Naujoks, T. Stewart, and J. Wallenius (eds.), Multiple Criteria Decision Making for Sustainable Energy and Transportation Systems. Lecture Notes in Economics and Mathematical Systems, Vol. 634. Springer, Berlin and Heidelberg, Germany. https://doi.org/10.1007/978-3-642-04045-0_9.

Solinen, E., and C. Palmqvist. 2023. Development of new railway timetabling rules for increased robustness. Transport Policy, Vol. 133, pp. 198–208. https://doi.org/10.1016/j.tranpol.2023.02.003.

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Zieger, S., N. Weik, and N. Nießen. 2018. The influence of buffer time distributions in delay propagation modelling of railway networks. Journal of Rail Transport Planning & Management, Vol. 8, Issues 3–4, pp. 220–232. https://doi.org/10.1016/j.jrtpm.2018.09.001.

Suggested Citation: "References." National Academies of Sciences, Engineering, and Medicine. 2026. Operating Margin and Recovery Factor Practices for Travel Time Estimation and Rail Scheduling. Washington, DC: The National Academies Press. doi: 10.17226/29463.

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Suggested Citation: "References." National Academies of Sciences, Engineering, and Medicine. 2026. Operating Margin and Recovery Factor Practices for Travel Time Estimation and Rail Scheduling. Washington, DC: The National Academies Press. doi: 10.17226/29463.
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Suggested Citation: "References." National Academies of Sciences, Engineering, and Medicine. 2026. Operating Margin and Recovery Factor Practices for Travel Time Estimation and Rail Scheduling. Washington, DC: The National Academies Press. doi: 10.17226/29463.
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