Parallel simulation of high-speed trains controlled by radio block centers using Spark cloud

Train movement prediction simulation is an effective method of enhancing operation safety and efficiency railway transportation. data generated by the trains running in a network are huge, on other hand, quantity from processing also explosively increased for analysis decision such as conflict recognition scheduling optimization, which greatly increases time cost simulation. This paper attempts to propose train model driven authorities (MAs) issued radio block centers (RBCs) its parallel algorithm realized Spark cloud. provides solution iterative computing dynamic process based Different general big independent datasets, resilient distributed datasets expandable along processes. The Dataframe SparkSQL modules Apache employed handle problems usage interdependency datasets. Scala language that used build platform. results high-speed demonstrates proposed can achieve theoretical rationality decrease satisfy real-time performance.