Skip to main content
SpringerLink
Log in

Centralized Monitoring System of Rail Transit Multiple Signals Based on Bus Technology

  • Conference paper
  • First Online:
Advanced Hybrid Information Processing (ADHIP 2023)

Included in the following conference series:

  • 30 Accesses

Abstract

Conventional rail transit signal monitoring systems are prone to being affected by pooling aggregation during image downsampling processing, resulting in abnormal monitoring functions. Therefore, this study designs a new centralized monitoring system for multi-channel signals in rail transit based on bus technology. In the hardware part of the system, SBMA RF receiver, SZ45XIT magnetic random access memory, and SPACECOM electric zoom monitoring camera are installed to support smooth operation of the system. In the system software section, based on the design of traffic multi-channel monitoring signal processing algorithms, a signal centralized monitoring function module was generated based on bus technology. The test results indicate that the various functions of the system operate in an orderly manner, with reliability and application value. In addition, compared to traditional systems, the signal monitoring delay of this system is lower.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 99.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Velmurugan, P., Ashok, B.: Improving the quality of service by continuous traffic monitoring using reinforcement learning model in VANET. Int. J. Model. Simul. Sci. Comput. 13(06), 310–327 (2022)

    Article  Google Scholar 

  2. Meng, B., Damanhuri, N.S., Othman, N.A.: Smart traffic light control system using image processing. IOP Conf. Ser. Mater. Sci. Eng. 1088(1), 01–08 (2021)

    Article  Google Scholar 

  3. Saldivar-Carranza, E.D., Hunter, M., Li, H., et al.: Longitudinal performance assessment of traffic signal system impacted by long-term interstate construction diversion using connected vehicle data. J. Transp. Technol. 4, 11–20 (2021)

    Google Scholar 

  4. Yao, J., Qiu, J.: Research on road traffic flow prediction based on SSA-BP algorithm. J. Southwest Univ. (Natural Science Edition) 44(10), 193–201 (2022)

    Google Scholar 

  5. Liu, Z., Cao, Y., Sha, A., et al.: Energy harvesting array materials with thin piezoelectric plates for traffic data monitoring. Constr. Build. Mater. 302(4), 124–136 (2021)

    Google Scholar 

  6. Sofuoglu, S.E., Aviyente, S.: GLOSS: tensor-based anomaly detection in spatiotemporal urban traffic data. Sig. Process. Off. Publ. Euro. Assoc. Sig. Process. (EURASIP) 192 (2022)

    Google Scholar 

  7. Singleton, P.A., Runa, F.: Pedestrian traffic signal data accurately estimates pedestrian crossing volumes. Transp. Res. Rec. 2675(6), 429–440 (2021)

    Article  Google Scholar 

  8. Nawaz, A., Zafar, N.A., Alkhammash, E.H.: Formal modeling of responsive traffic signaling system using graph theory and VDM-SL. Sustainability 13 (2021)

    Google Scholar 

  9. Cao, B., Liu, W., Zhang, L., et al.: Simulation analysis of signal coverage of ADS-B base station based on DEM. J. Phys. Conf. Ser. 1865(4), 1–8 (2021)

    Article  Google Scholar 

  10. Zhu, J., et al.: Lightweight web visualization of massive road traffic data. J. Southwest Jiaotong Univ. 56(05), 905–912 (2021)

    Google Scholar 

  11. Pan, C.: Frequencyshift rail transit signal detection method based on time-frequency analysis. Mach. Elec. 40(01), 71–75 (2022)

    Google Scholar 

  12. Sun, M., Wei, H., Li, X., Yu, J., Xu, L.: Refined traffic state detection of road based on multidimensional density clustering. J. Geomat. Sci. Technol. 36(04), 412–417 (2019)

    Google Scholar 

  13. Zhu, L.: Intelligent wireless signal monitoring of urban rail transit CBTC system. Urban Mass Transit 24(S1), 117–121 (2021)

    Google Scholar 

  14. Yu, J.: Research on architecture of urban rail transit signaling system. Urban Mass Trans. 25(10), 131–135+143 (2022)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Wuhan Railway Vocational College of Technology, Wuhan, 430000, China

    Bo Li

Authors
  1. Bo Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Bo Li .

Editor information

Editors and Affiliations

  1. Harbin Engineering University, Harbin, China

    Lin Yun

  2. Harbin Engineering University, Harbin, China

    Jiang Han

  3. Harbin Engineering University, Harbin, China

    Yu Han

Rights and permissions

Reprints and permissions

Copyright information

© 2024 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Li, B. (2024). Centralized Monitoring System of Rail Transit Multiple Signals Based on Bus Technology. In: Yun, L., Han, J., Han, Y. (eds) Advanced Hybrid Information Processing. ADHIP 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 549. Springer, Cham. https://doi.org/10.1007/978-3-031-50549-2_26

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-50549-2_26

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-50548-5

  • Online ISBN: 978-3-031-50549-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation