A high-speed railway network dataset from train operation records and weather data

The operation data of trains on high-speed railway network are rich resources in the transportation field. With the development of high-speed railway, large amounts of data are generated, and research on train performance based on the real data has become a trend. However, most research is still based on simulated or partial data due to the difficulty of obtaining the train operation data. To support the research in the transportation filed, we develop a high-speed railway network dataset, containing the train operation data from October 8, 2019 to January 27, 2020 and the train delay data of the railway stations passing by these trains. In the dataset, weather, temperature, wind power and major holidays are considered as factors affecting train operation. The dataset can be used to solve various decision-making problems, such as real-time dispatching, train operation diagram adjustment and intelligent driving assistance. Potential research values include but are not limited to delay propagation analysis, train delay and recovery prediction and research on the robustness of train operation diagrams.高速铁路网列车运行数据是交通运输领域的宝贵资源。随着高速铁路的发展，海量运行数据随之产生，基于真实运营数据开展列车性能相关研究已成为行业趋势。然而，由于列车运行数据获取难度较大，当前多数研究仍基于模拟数据或局部真实数据开展。为支撑交通运输领域的相关研究，本团队构建了一套高速铁路网数据集，涵盖2019年10月8日至2020年1月27日的列车运行数据，以及上述列车途经车站的列车晚点数据。该数据集纳入了影响列车运行的多类因子，包括天气、气温、风力等级及法定节假日等。本数据集可用于解决各类轨道交通决策问题，例如实时调度、列车运行图调整以及智能驾驶辅助等场景。其潜在研究价值包括但不限于晚点传播分析、列车晚点与恢复预测，以及列车运行图鲁棒性研究等方向。