Design and Implementation of General Aviation Cooperative Airspace Planning Algorithm Based on K-means Clustering

With the continuous development of the general aviation industry, the reasonable allocation of the general aviation cooperative airspace is the key to its efficient and safe operation. However, the current collaborative airspace based on human cognition and experience cannot satisfy the rapid development of the current general aviation industry chain in terms of efficiency and convenience. In response to this problem, a K-means algorithm is proposed to use the cluster analysis of massive historical ADS-B surveillance data to calculate the airspace range with high utilization rate and intensive general aircraft, and provide assistance for the airspace planning of the low-altitude operation center, as well as decision making.