基于区块链的安全众测,用于铁路信号数据准备中的轨道侧基础设施信息收集和验证

IET Blockchain Pub Date : 2021-05-10 DOI:10.1049/blc2.12002
Ganesan Muniandi
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引用次数: 1

摘要

世界各地的铁路运营商都在采用先进的铁路信号和列车保护控制系统,以提高其安全性能。在这些重新发送信号的项目中,关于已经安装的信号、点阵机、轨道电路等沿着轨道基础设施的信息对于配置先进的信号设备是必不可少的。传统的基于无人机、直升机等的信息采集方法在隧道、丘陵地区、河流桥梁、茂密森林等地形中存在访问限制。为了克服这些挑战,本文提出了一组列车参与信息收集,另一组列车确认所收集信息的有效性的铁路车辆群体感知方法。对于列车与中心化服务器之间的信息交换,本研究选择了基于区块链的许可信息交易机制,以保证列车的可信度。此外,还包括基于铁路标记语言的区块链数据库,用于信息不变性、人群信息集成和数据准备信令规则的自动执行。最后,进行了案例研究,以分析在提议的信号数据准备过程中,基于众感的安全轨道侧基础设施信息收集和验证、允许的区块链支持的信息交易和区块链数据库的拟议组合的充分性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Blockchain-enabled secure crowdsensing for trackside infrastructure information collection and validation in railway signalling data preparation

Blockchain-enabled secure crowdsensing for trackside infrastructure information collection and validation in railway signalling data preparation

Rail operators around the world are adopting advanced control systems for railway signalling and train protection to improve their safety performance. In these re-signalling projects, the information about the already installed signals, point machines, track circuits etc. along the trackside infrastructure is essential for the configuration of advanced signalling equipment. The conventional information collection method which is based on unmanned aerial vehicles, helicopters etc. has the access limitations in terrains such as tunnels, hilly regions, river bridges, dense forests etc. To overcome these challenges, this paper proposes the railway vehicular crowdsensing method in which one group of trains participates in this information collection and another group of trains confirms the validity of the collected information. For information exchange between the trains and centralized server, this study chooses the permissioned blockchain-based information transaction mechanism to ensure the trustworthiness. Furthermore, the railway markup language-based blockchain databases are included for information immutability, crowd information integration, and the automatic execution of data preparation signalling rules. Finally, the case studies are carried out to analyse the adequacy of the proposed combination of crowdsensing based secure trackside infrastructure information collection and validation, permissioned blockchain-enabled information transaction and blockchain databases in the proposed signalling data preparation process.

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