With the gradual maturity of the automatic train operation (ATO) system in subways, its application scope has also expanded to the high-speed railway field. Considering that the ATO system is still in the early stages of operation, it will take time to fully mature, and definite specifications of the requirements for system operation have not yet been formed. This paper presents the operational design domain (ODD) of the high-speed railway ATO system and proposes a scenario analysis method based on the operational design domain to obtain the input conditions of the system requirements. The article models and verifies the scenario of the linkage control of the door and platform door based on the UPPAAL tools and extracts the input and expected output of the system requirements of the vehicle ATO system. Combined with the input conditions of the system requirements, the system requirements of the vehicle ATO in this scenario are finally obtained, which provides a reference for future functional specification generation and test case generation.

Whether in Europe or China, ATO based train control system has become a trend. However, the application time of ATO is short and the user experience is insufficient. In order to better carry out system research and development, system test, system optimization and other work, the construction scheme of the simulation platform based on digital twin is proposed. In this paper, by comparing five-dimension model with three-dimension model, digital twin is built based on the five-dimension model of digital twin, and the virtual model in the five-dimension model is introduced in detail. Physical, behavioural, rule and geometric models are constructed from the four perspectives of the effect of each element in the scene on the train, the dynamic characteristics of the train, the correlation between the elements and the scene, and the visualization of the scene. Based on digital twin, the paper designs the framework of simulation platform to support ATO performance optimization and other work. The parameters in the model can be adjusted repeatedly through field data to achieve higher consistency between the model and the simulation object.