The moving block mode based traditional running route tracking method of urban rail train has the problems of delay diffusion and poor restoration capability of the running route under the condition of mass passenger flow and traffic flow. Therefore,a big data analysis based running route tracking method of city rail train is proposed. The big data running method of Map/Reduce parallel computing architecture is constructed on the basis of Hadoop framework. The task allocation and task distri-bution of Map stage,and task combination and data storage of Reduce stage are performed to study,analyze and store the run-ning data of city rail train. The train running planning model based on maximum algebra is constructed. On the basis of analyzing the model parameters,the constraint condition of the train operation planning model was designed to obtain the linear model of the train operation planning in the maximum algebra,and realize the rational running route planning of urban rail train in big data environment. The experimental results show that the proposed method can control the train pass smoothly and ensure the uniform and stable operation of the train,and has the strong regulation for passenger flow.%传统基于移动闭塞模式下的城轨列车运行路线追踪方法在面向海量人流和车流的情况下,存在延误扩散以及线路运行的恢复能力差等问题.因此,提出基于大数据分析的城轨列车运行路线追踪方法,在Hadoop架构下塑造Map/Re-duce并行计算架构的大数据运行方法,通过Map阶段任务配置与分发以及Reduce阶段任务合并与数据存储,对城轨列车运行数据进行学习、分析以及存储,塑造基于极大代数的列车运行计划模型,在分析模型参数的基础上,设计列车运行计划模型的约束条件,得到列车运行计划在极大代数中的线性模型,实现大数据环境下城轨列车运行路线的合理规划.实验结果表明,运用此方法的列车可顺利通行,对客流具有较强的调控性,确保列车均匀稳定地运行.
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