A Bayesian Game-Based Train Protection Method Using Train-to-Train Communication
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
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.
Details
Original language | English |
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Article number | 10.1109/MITS.2021.3075840 |
Pages (from-to) | 2-13 |
Number of pages | 12 |
Journal | IEEE Intelligent Transportation Systems Magazine |
Volume | 14 |
Issue number | 4 |
Publication status | Published - 3 Jun 2021 |
Peer-reviewed | Yes |
External IDs
Scopus | 85107386431 |
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ORCID | /0000-0002-6853-0361/work/142242276 |