A high-speed railway network dataset from train operation records and weather data
Dalin Zhang, Yunjuan Peng, Yi Xu, Chenyue Du, Yumei Zhang, Nan Wang, Yunhao Chong, Hongwei Wang, Daohua Wu, Jintao Liu, Hailong Zhang, Lingyun Lu, Jiqiang Liu
Abstract
High-speed train operation data are reliable and rich resources in data-driven research. However, the data released by railway companies are poorly organized and not comprehensive enough to be applied directly and effectively. A public high-speed railway network dataset suitable for research is still lacking. To support the research in large-scale complex network, complex dynamic system and intelligent transportation, we develop a high-speed railway network dataset, containing the train operation data in different directions from October 8, 2019 to January 27, 2020, the train delay data of the railway stations, the junction stations data, and the mileage data of adjacent stations. In the dataset, weather, temperature, wind power and major holidays are considered as factors affecting train operation. Potential research values of the dataset include but are not limited to complex dynamic system pattern mining, community detection and discovery, and train delay analysis. Besides, the dataset can be used to solve various railway operation and management problems, such as passenger service network improvement, train real-time dispatching and intelligent driving assistance.