城市轨道交通移动闭塞列控系统列车追踪间隔研究
闫丽霞1高云波1李云骢2
Train Tracking Interval of Moving Block Train Control System in Urban Rail Transit
YAN LixiaGAO YunboLI Yuncong
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作者信息:1.兰州交通大学自动化与电气工程学院，730070,兰州；
2.北京通号城市轨道交通技术有限公司，100070,北京
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Affiliation:School of Automation and Electrical Engineering, Lanzhou Jiaotong University, 730070, Lanzhou, China
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关键词:
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Key words:
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DOI:10.16037/j.1007-869x.2020.03.009
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中图分类号/CLCN:U231.7
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栏目/Col:研究报告
摘要:
目前，基于通信的移动闭塞列控系统作为轨道交通列控系统的主要发展方向，在一定程度上缩短了列车之间的追踪间隔。追踪间隔的计算是列车生成移动授权的前提。列控系统中移动授权的发布由区域控制器来完成。列控系统中由于追踪模式的不同，列车追踪间隔也会有差异，从而影响移动授权生成，影响行车效率。分析了列车移动授权生成原理，研究了列车区间追踪场景下绝对追踪模式和相对追踪模式下的列车追踪间隔，并进行了仿真。仿真分析结果表明：相对追踪模式下列车生成的移动授权更大，可以进一步缩小列车追踪间隔；绝对追踪模式存在最优追踪速度。
Abstracts:
At present, the moving block train control system based on communication represents the main development direction of rail transit train control system, which shortens the train tracking interval to some extent. The calculation of the tracking interval is a prerequisite for the train to generate the mobile authorization, and the release of which in the train control system is completed by the zone controller (ZC). Due to different tracking modes in train control system, the train tracking intervals are also different, which will affect the generation of mobile authorization and the train operation efficiency. In this paper, the principle of train movement authorization generation is analyzed, the train tracking interval under absolute tracking mode and relative tracking mode in the train interval tracking scenario are studied and simulated respectively. The simulation analysis results show that the relative tracking mode can further reduce the train tracking interval, while the absolute tracking mode has the optimal tracking speed.
引文 / Ref:
闫丽霞，高云波，李云骢.城市轨道交通移动闭塞列控系统列车追踪间隔研究[J].城市轨道交通研究，2020，23（3）：34.
YAN Lixia，GAO Yunbo，LI Yuncong.Train Tracking Interval of Moving Block Train Control System in Urban Rail Transit[J].Urban mass transit，2020，23（3）：34.
YAN Lixia，GAO Yunbo，LI Yuncong.Train Tracking Interval of Moving Block Train Control System in Urban Rail Transit[J].Urban mass transit，2020，23（3）：34.
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