Study on evolution characteristics of air traffic situation complexity based on complex network theory

This study proposed a new method to describe air traffic situations based on the theory of complex networks and elaborate its evolutionary laws, expecting to reveal the basic characteristics of air traffic complexity. Based on 2D complexity and 3D complexity, a double-layer multistage dynamic network model was built and an air traffic complexity vector was proposed. The real flight data from four traffic control sectors were used to characterize statistically the evolution of air traffic situations. Results show that the complexity vector helps to describe the structural characteristics of air traffic situations and identify the evolutionary characteristics of different traffic situations. Based on k-means, air traffic situations were classified into three complexity patterns. The frequency of occurrence, life cycle, and transition probability of complexity patterns were statistically calculated. Results show that the traffic situations of high-altitude sectors bring more 2D complexity and less 3D complexity than those of low-altitude sectors. In most cases, the four sectors belong to medium complexity or below, and a specific complexity pattern appears in a certain period with a specific probability. The life cycle of air traffic complexity patterns is usually on the order of seconds or minutes and differs slightly among patterns. Transition probabilities of patterns indicate that the air traffic situation is evolving stably on the whole, but will probably runs into severe change.