列车自动驾驶(ATO)技术在我国高速铁路与城际铁路已经得到应用，为研究ATO驾驶模式对车站追踪间隔的影响，基于京沈客专ATO测试试验，收集了调度所实时CTC数据、随车记录数据及车载ATO数据，利用mathlab对车载ATO试验数据进行处理分析，得出列车运行VS曲线，将VS曲线分解到列车车站出发及到达各个环节，分析ATO与人工两种驾驶模式下车站出发与到达各个环节的时间。对比人工驾驶模式，ATO模式下控车更加精准，ATO驾驶模式下的出发追踪间隔较人工驾驶模式更短但压缩效果不明显；如果ATO系统在进站信号机前不设置固定限速、进站走行阶段不采取降速策略，到达追踪间隔较人工驾驶模式可以实现压缩。
ATO technology has been applied in China’s high-speed railways and intercity railways. In order to study the influence of ATO operation mode on station interval time, real-time CTC data of dis-patching station, manual recording data on train and on-board ATO data were collected based on the ATO experiment of Beijing-Shengyang High Speed Railway. And the train operation VS curves were obtained by using mathlab to process and analyze the on-vehicle ATO test data. The VS curves are decomposed into train station departure and arrival links, and the time of station departure and arrival links are analyzed under ATO and manual operation modes. ATO operation mode is more accurate compared with manual operation mode. The departure intervaltime of ATO operation mode is shorter than manual operation model but the compression effect is not obvious. If the ATO system does not set a fixed speed limit before the entry signal, and does not take a speed reduction strategy during the station arrival running phase, the arrival interval time can be compressed compared to the manual driving mode.
