Real-Time Evaluation Model of Urban Rail Train Communication Network

  • Yin Tian
  • Honghui Dong
  • Limin Jia
  • Yong Qin
  • Shao huang Pang
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 287)

Abstract

In addition to the traditional TCN, both the train communication networks based on Ethernet and WSNs are also applied, to some extent, in metros. The real time is a decisive indicator of communication network in metro trains. To address such index, this paper develops an evaluative model to comprehensively analyze it and compares the Real-Time of different communication networks. Supported by practical examples, we conclude that this model functions effectively and accurately.

Keywords

Train communication network Real Time MVB Ethernet 

Notes

Acknowledgments

This work is supported by the National High-Tech Research and Development Program of China “863 Project” (Grant No. 2011AA110505), the State Key Laboratory of Rail Traffic Control and Safety (Contract No. RCS2010ZT004), and the Star of Science and Technology Program of Beijing (Grant Z1211106002512027).

References

  1. 1.
    Chaoyong G (2012) Research on several issues of high-speed electric multiple units train network control. Beijing Jiaotong University, BeijingGoogle Scholar
  2. 2.
    Li W, Chen T (2001) Research and analysis of the real-time character of locomotive distributed control system based on train communication network. Comput Meas Control 10Google Scholar
  3. 3.
    Almeida, Luís M (2002) DET-IEETA, Aveiro Univ., Portugal Pedreiras, Paulo; Fonseca, José Alberto G (The FTT-CAN protocol: why and how). IEEE Trans Ind Electron (49):1189–1201Google Scholar
  4. 4.
    Bibinagar N, Kim W (2013) Switched ethernet-based real-time networked control system with multiple-client-server architecture. IEEE-ASME Trans Mechatron 1:104–112CrossRefGoogle Scholar
  5. 5.
    Vitturi S, Seno L, Tramarin F, Bertocco M (2013) On the rate adaptation techniques of IEEE 802.11 networks for industrial applications. IEEE Trans Industr Inf 1:198–208Google Scholar
  6. 6.
    Robert J, Georges JP, Rondeau E, Divoux T (2012) Minimum cycle time analysis of ethernet-based real-time protocols. Int J Compute Comm Control 4:743–757Google Scholar
  7. 7.
    Na H (2011) The wireless sensor network monitoring system of high-speed railway. Dalian University of Technology Electronic, DalianGoogle Scholar
  8. 8.
    Mahasukhon P (2011) A study on energy efficient multi-tier multi-hop wireless sensor networks for freight-train monitoring. In: 2011 7th international wireless communications and mobile computing conference (IWCMC), pp 279–301Google Scholar
  9. 9.
    Aguado M, Jacob E, Sáiz P, Unzilla JJ, Higuero MV, Matías J (2005) In railway signaling systems and new trends in wireless data communication. IEEE 2005:1333–1336Google Scholar
  10. 10.
    Kanamori H (2005) Real-time seismology and earthquake damage mitigation. Annu Rev Earth Planet Sci 33:195–214 Google Scholar
  11. 11.
    Kitahara F, Kera K, Bekki K (2000) In autonomous decentralized traffic management system. IEEE 2000:87–91Google Scholar
  12. 12.
    Chang C, Xu D, Quek H (1999) In Pareto-optimal set based multiobjective tuning of fuzzy automatic train operation for mass transit system. IET 1999:577–583Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Yin Tian
    • 1
  • Honghui Dong
    • 1
  • Limin Jia
    • 1
  • Yong Qin
    • 1
  • Shao huang Pang
    • 2
  1. 1.State Key Laboratory of Rail Traffic Control and SafetyBeijing Jiaotong UniversityBeijingChina
  2. 2.Guangzhou Metro CorporationBeijingChina

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