A Bayesian Game-Based Train Protection Method Using Train-to-Train Communication

Train-to-wayside communication cannot satisfy growing demands for safety and efficiency on high-speed railways. In this article, a novel train control system is presented based on train-to-train (T2T) communication and mobile edge computing (MEC). The T2T approach can shorten communication times and optimize the control performance. The scheme is described and compared to the traditional communication system, considering parameters that can result in poor service quality. Additionally, the application of MEC is introduced in a novel wireless access network. Then, a Bayesian game-based protection method is proposed to ensure operation safety and efficiency. Considering bit errors, packet losses, and broken connections, train and communication system cost functions are designed. The results show that the proposed strategy can reduce the impact of unreliable communication on the safe operation of trains.

• Record URL:
  http://dx.doi.org/10.1109/MITS.2021.3075840
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/19391390
• Supplemental Notes:
  • Copyright © 2022, IEEE.
• Authors:
  • Wu, Wei
  • Song, Haifeng
  • Zhang, Zixuan
  • Zhang, Shiyao
  • 0000-0002-9856-2444
  • Trinckauf, Jochen
  • Dong, Hairong
• Publication Date: 2022-7

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 202-213
• Serial:
  • IEEE Intelligent Transportation Systems Magazine
  • Volume: 14
  • Issue Number: 4
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
  • ISSN: 1939-1390
  • Serial URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5117645

Subject/Index Terms

• TRT Terms: Communication; High speed rail; Mobile computing; Railroad safety; Train operations; Vehicle to vehicle communications
• Subject Areas: Data and Information Technology; Operations and Traffic Management; Railroads; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01857562
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 14 2022 9:11AM