交通运输系统工程与信息 ›› 2016, Vol. 16 ›› Issue (5): 85-89.

• 智能交通系统与信息技术 • 上一篇    下一篇

基于贝叶斯原理的车次号追踪方法

袁志明1,张琦*2,黄康2,陈峰2   

  1. 1. 中国铁道科学研究院,北京100081;2. 中国铁道科学研究院通信信号研究所,北京100081
  • 出版日期:2016-10-25 发布日期:2016-10-25
  • 作者简介:袁志明(1980-),男,山东泰安人,副研究员,博士生.
  • 基金资助:

    中国铁道科学研究院基金/China Academy of Railway Sciences Foundation Project(2015YJ054).

A Bayesian Method for Train Number Tracking in Railway Network

YUAN Zhi-ming1, ZHANG Qi2, HUANG Kang2, CHEN Feng2   

  1. 1. China Academy of Railway Sciences, Beijing 100081, China; 2. Signal & Communication Research Institute, China Academy of Railway Sciences, Beijing 100081, China
  • Online:2016-10-25 Published:2016-10-25

摘要:

在铁路行车调度指挥中,需要实时掌握列车在路网中的实际位置.本文对承载 列车位置信息的车次号追踪方法的实现和优化进行研究.在分析车次号追踪问题基础上 给出了问题的数学描述和依赖于信号状态及列车行车计划的车次号基本追踪模型,并在 此基础上,构建了基于贝叶斯原理的车次号追踪优化方法和模型.采用津秦高速铁路数据 对实现的车次号追踪模型进行仿真和分析,并对车次号追踪模型在各种约束下的实现结 果进行比较分析.结果表明,该优化的车次追踪算法能有效地降低车次号追踪的误判,具 有良好的容错性和鲁棒性.

关键词: 铁路运输, 车次号追踪, 贝叶斯原理, 列车, 列车位置预测

Abstract:

It is necessary to get the train position in the railway network in real time for the railway traffic control. This paper investigates implementation and optimization method of train number tracking, by which the train position information can be captured. According to the characters of the train number tracking problem, the mathematical description of the problem and the tracking model based on railway signal states and train schedule are proposed. Then a method using Bayesian principle is proposed to make improvement. The data of Tianjin-Qinhuangdao Railway is used to make simulation for the train number tracking model. The simulation result is compared with results which are obtained under some restrictions and some analysis are discussed. The results show that the proposed method can effectively improve the accuracy of train number tracking and with better fault-tolerant robustness.

Key words: railway transportation, train number tracking, Bayesian principle, train, train position prediction

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