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基于虚拟耦合的列车群体智能控制技术研究及展望
引用本文:刘岭. 基于虚拟耦合的列车群体智能控制技术研究及展望[J]. 铁路通信信号工程技术, 2020, 0(2): 1-9
作者姓名:刘岭
作者单位:北京全路通信信号研究设计院集团有限公司;北京市高速铁路运行控制系统工程技术研究中心
摘    要:铁路列车运行控制方式经历了固定闭塞、准移动闭塞和移动闭塞的发展过程,随着车联网和群体智能等新一代信息技术的快速发展,更高效率的先进列车运行控制技术成为研究热点。面向下一代铁路列车运行控制系统,研究一种基于虚拟耦合的列车群体协同运行控制技术,提出采用多智能体系统(MAS)对虚拟耦合列车群的运行进行控制的方法,刻画其控制规则并构建以列车群稳定协同运行为目标的控制模型。在此基础上,设计基于虚拟耦合的列车控制及调度系统框架,采用仿真技术验证该方法可大幅缩短列车运行间隔,提升运行控制效率。最后分析总结基于群体智能的列车运行控制技术研究及发展方向。

关 键 词:列车群  运行控制  虚拟耦合  多智能体

Research and Prospect of Intelligent Control Technology for Virtually Coupled Train Formation
Liu Ling. Research and Prospect of Intelligent Control Technology for Virtually Coupled Train Formation[J]. Railway Signalling & Communication Engineering, 2020, 0(2): 1-9
Authors:Liu Ling
Affiliation:(CRSC Research&Design Institute Group Co.,Ltd,Beijing 100070,China;Beijing Engineering Technology Research Center of Operation Control Systems for High Speed Railways,Beijing 100070,China)
Abstract:Train operation control method has gone through the development of fixed block, quasimoving block and moving block. With rapid development of a new generation of information technology, such as vehicle networking and swarm intelligence, advanced train operation control technology with more efficient becomes hotspots. Orienting the next generation of train operation control system, this paper researches on a kind of collaborative intelligent control technology of train based on virtual coupling. This paper proposes the method to control the operation of a virtual coupled train group using multi-agent system(MAS), and describes its control rules and built train group in order to stabilize control model aiming for collaborative operation. On this basis, train control and dispatching system framework are designed based on virtual coupling. Using simulation technology to verify the method can reduce train operation intervals and improve operation control efficiency. Finally, this paper analyzes and summarizes the research and development direction of train operation control technology based on swarm intelligence.
Keywords:train formation  operation control  virtual coupling  multi-agent
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