Monday dataset 和 aerodrome dataset

本研究开发了两个数据集，分别是Monday dataset和aerodrome dataset，用于训练和评估航空碰撞风险模型。Monday dataset包含104个周一的数据，覆盖全球范围，用于训练不接受空中交通控制服务的飞机模型。Aerodrome dataset则是基于机场周边环境的新数据集，专注于机场终端区域的飞机行为，支持RTCA SC-228标准的发展。两个数据集均通过高性能计算资源处理，利用了MIT Lincoln Laboratory Supercomputing Center的计算能力。数据集的创建和处理过程涉及复杂的组织和优化，旨在提高处理效率和模型训练的准确性。这些数据集主要应用于航空安全研究，特别是无人机系统与有人机系统的碰撞风险评估。

This study developed two datasets, namely the Monday dataset and the aerodrome dataset, for training and evaluating aviation collision risk models. The Monday dataset contains data from 104 Mondays with global coverage, and is utilized for training models for aircraft not receiving air traffic control services. The aerodrome dataset is a novel dataset based on airport surrounding environments, focusing on aircraft behaviors in airport terminal areas and supporting the development of the RTCA SC-228 standard. Both datasets were processed using high-performance computing resources, leveraging the computational power of the MIT Lincoln Laboratory Supercomputing Center. The creation and processing of these datasets involve complex organization and optimization, aiming to improve processing efficiency and the accuracy of model training. These datasets are primarily applied in aviation safety research, especially in collision risk assessment between unmanned aerial systems (UAS) and manned aircraft systems.