Skip to main content
Log in

A simulation model for estimating train and passenger delays in large-scale rail transit networks

  • Published:
Journal of Central South University Aims and scope Submit manuscript

Abstract

A simulation model was proposed to investigate the relationship between train delays and passenger delays and to predict the dynamic passenger distribution in a large-scale rail transit network. It was assumed that the time varying original-destination demand and passenger path choice probability were given. Passengers were assumed not to change their destinations and travel paths after delay occurs. Capacity constraints of train and queue rules of alighting and boarding were taken into account. By using the time-driven simulation, the states of passengers, trains and other facilities in the network were updated every time step. The proposed methodology was also tested in a real network, for demonstration. The results reveal that short train delay does not necessarily result in passenger delays, while, on the contrary, some passengers may get benefits from the short delay. However, large initial train delay may result in not only knock-on train and passenger delays along the same line, but also the passenger delays across the entire rail transit network.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. NIELSEN O A, LANDEX O, FREDERIKSEN R D. Passenger delay models for rail networks [M] Schedule-Based Modeling of Transportation Networks. Springer US, 2009: 27–49.

  2. CAREY M, KWIECINSKI A. Properties of expected costs and performance measures in stochastic models of scheduled transport [J]. European Journal of Operational Research, 1995, 83(1): 182–199.

    Article  MATH  Google Scholar 

  3. CAREY M. Exante heuristic measures of schedule reliability [J]. Transportation Research Part B: Methodological, 1999, 33(7): 473–494.

    Article  MathSciNet  Google Scholar 

  4. CAREY M. Optimizing scheduled times, allowing for behavioral response [J]. Transportation Research Part B: Methodological, 1998, 32(5): 329–342.

    Article  Google Scholar 

  5. HALLOWELL S F, HARKER P T. Predicting on-time performance in scheduled railroad operations: methodology and application to train scheduling [J]. Transportation Research Part A: Policy and Practice, 1998, 32(4): 279–295.

    Article  Google Scholar 

  6. HIGGINS A, KOZAN E. Modeling train delays in urban networks [J]. Transportation Science, 1998, 32(4): 46–357.

    Article  Google Scholar 

  7. HUISMAN T, BOUCHERIE R J. Running times on railway sections with heterogeneous train traffic [J]. Transportation Research Part B: Methodological, 2001, 35(3): 271–292.

    Article  Google Scholar 

  8. YUAN J, HANSEN I A. Optimizing capacity utilization of stations by estimating knock-on train delays [J]. Transportation Research Part B: Methodological, 2007, 41(2): 202–217.

    Article  Google Scholar 

  9. MEESTER L E, MUNS S. Stochastic delay propagation in railway networks and phase-type distributions [J]. Transportation Research Part B: Methodological, 2007, 41(2): 218–230.

    Article  Google Scholar 

  10. GOVERDE R M P. A delay propagation algorithm for large-scale railway traffic networks [J]. Transportation Research Part C: Emerging Technologies, 2010, 18(3): 269–287.

    Article  Google Scholar 

  11. MURALI P. DESSOUKY M. PALMER K. MURALI P DESSOUKY M, ORDONEZ F, PALMER K. A delay estimation technique for single and double-track railroads [J]. Transportation Research Part E: Logistics and Transportation Review, 2010, 46(4): 483–495.

    Article  Google Scholar 

  12. JIANG Zhi-bin, XU Rui-hua, XIE Chao. Train delay propagation simulation in rail transit system [C]// The 1st International Conference on Transportation Engineering. Reston: American Society of Civil Engineers, 2007: 789-794.

    Google Scholar 

  13. JIANG Zhi-bin, XIE Chao. Multi-agent delay simulation model in mass rail transit system [C]// 2009 International Conference on Measuring Technology and Mechatronics Automation. Los Alamitos: IEEE Computer Society, 2009: 717–720.

    Chapter  Google Scholar 

  14. JIANG Zhi-bin, Jin Yi, Chen Jing-jing. Running buffer time distribution calculation based on delay analysis in mass transit system [C]// The 2nd International Conference on Transportation Engineering. Reston: American Society of Civil Engineers, 2009: 4068–4073.

    Chapter  Google Scholar 

  15. JIANG Zhi-bin, GAO Jia, Xu Rui-hua. Circle rail transit line timetable scheduling using Rail TPM [C]// Computers in Railways XII: Computer System Design and Operation in Railways and Other Transit Systems. Southampton: WIT Press, 2010: 945–952.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Feng Li  (李锋).

Additional information

Foundation item: Project(51008229) supported by the National Natural Science Foundation of China; Project supported by Key Laboratory of Road and Traffic Engineering of Tongji University, China

Rights and permissions

Reprints and permissions

About this article

Cite this article

Jiang, Zb., Li, F., Xu, Rh. et al. A simulation model for estimating train and passenger delays in large-scale rail transit networks. J. Cent. South Univ. 19, 3603–3613 (2012). https://doi.org/10.1007/s11771-012-1448-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11771-012-1448-9

Key words

Navigation