Functional Model Analysis of Level Transition Process of CTCS-3 System

  • You ZhouEmail author
  • Tao He
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1060)


In the process of level transition between C3 and C2 based on CTCS-3 level control system, Unified Modeling Language (UML) and Colored Petri Net (CPN) model the conversion process, which are used to ensure the consistency between the train control system and model. The model data was extracted and analyzed by MATLAB. It analyzed the influence factors of train speed on the grade conversion rate, that was the time of the transition and the success rate of the level transition. The level conversion model is verified, indicating that the UML and CPN models meet the security and real-time requirements of the CTCS-3 level control system-level conversion scenario.


CTCS-3 UML CPN Model validation 



This work was financially supported by Gansu Research Center of Automation Engineering Technology for Industry & Transportation Open-end Funds 2019 (GSITA201902).


  1. 1.
    Zhang Y, Tang T. The modelling and formal analysis of RBC handover for CTCS-3 train control system based on colored Petri nets. J China Railway Soc. 2012;34(7):49–55.Google Scholar
  2. 2.
    Trowitzsch J, Zimmermann A. Using UML state machines and Petri nets for the quantitative investigation of ETCS. In: Proceedings of the 1st international conference on performance evaluation methodologies and tools. New York: ACM Press; 2006, Article No. 34.Google Scholar
  3. 3.
    Alur R, Etessami K, Yannakakis M. Inference of message sequence charts. IEEE Trans Softw Eng. 2003;29(7):623–33.CrossRefGoogle Scholar
  4. 4.
    Wang Y, Hu X, Chen Y. Modelling and simulation of transponder failure due to CTCS level conversion. Comput Eng Appl. 2016;52(8):234–9.Google Scholar
  5. 5.
    Wang J. Modeling and simulation of C2/C3 level transition in CTCS based on stochastic Petri net. Southwest Jiaotong University; 2015. p. 40–5.Google Scholar
  6. 6.
    Liang N, Wang H. Real-time performance analysis of RBC system for CTCS level 3 using stochastic Petri networks. J China Railway Soc. 2011;33(2):67–71.Google Scholar
  7. 7.
    Kang R, Wang J, Lyu J. UPPAAL-based modeling and verification of level transition process of high-speed railway train control system. J Beijing Jiaotong Univ. 2012;36(6):63–7.Google Scholar
  8. 8.
    Cao Y. The study on formal modelling and verification of high speed railway train control system. Beijing Jiaotong University; 2011. p. 20–3.Google Scholar
  9. 9.
    Liu J, Tang T, Zhao L. Functional safety analysis method for CTCS level 3 based on hybrid automata. Proceedings of the 15th international symposium on object/component/ service- oriented real-time distributed computing. Washington, D. C.; 2017. p. 7–12.Google Scholar
  10. 10.
    Liu J, Tang T, Zhao L. Functional safety analysis of CTCS-3 train control system based on UML model. J China Railway Soc. 2013;35(10):59–66.Google Scholar
  11. 11.
    Yang L, Zhang Y. Design of modelling of RBC handover based on UML and colored Petri nets. Comput Measur Control. 2012;20(4):1116–9.Google Scholar
  12. 12.
    Xu T, Zhao H, Tang T. Coloured-Petri-nets based reliability analysis of ETCS train radio communication. J China Railway Soc. 2008;30(1):38–42.Google Scholar
  13. 13.
    Li Y. Research on RBC level transition scenario based on directed graph and CPN. Lanzhou Jiaotong University; 2014. p. 33–5.Google Scholar
  14. 14.
    Zhang S. The overall technical scheme of CTCS-3 train control system. Beijing: China Railway Publishing House; 2010, p. 110–12.Google Scholar
  15. 15.
    Zhao J, Zhou J, Xing G. Research of translation UML activity diagram to Petri net. Comput Sci. 2014;41(7):143–7.Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.School of Automation & Electrical EngineeringLanzhou Jiao Tong UniversityLanzhouChina
  2. 2.Gansu Research Center of Automation Engineering Technology for Industry & TransportationLanzhouChina

Personalised recommendations