Research on Nonlinear Characteristics of Air Traffic Flows on Converging Air Routes

Insights into the temporal and spatial characteristics of air traffic flow is the prerequisite of air traffic flow simulation, prediction and control. Nonlinear characteristics of traffic flow time series on converging air routes were explored from the chaotic and fractal views. First, a traffic flow identification method based on air route network structure was proposed, and air traffic flow time series were constructed on different time scales. Then, based on the reconstruction of phase space, chaos existing in air traffic flow was quantitatively analyzed by the max Lyapunov exponent, and the chaotic characteristics of traffic flow time series on different time scales were analyzed by recurrent maps. Finally, the fractal characteristics of traffic flow time series on different time scales were analyzed using the correlation dimension. The results show that chaos does exist in traffic flow time series on different time scales. The chaotic characteristic of traffic flow time series is the most obvious at the time scale of 5 min. With time scales increasing, the randomness of air traffic flow time series increases, and the ability to show the system complexity becomes weak.