Delay propagation analysis based on an improved SIR infectious disease model

Abstract

To investigate the propagation mechanism of delays during the flight phase of aircraft operations, this paper proposes an improved Susceptible-Infected-Recovered (SIR) model-based method for delay propagation analysis. Firstly, the correlation between flight segments is calculated using the delay information of the flights that the segments pass through to determine the probability of delay propagation between segments. Then, the adjustments made by air traffic controllers after the occurrence of delays are simulated, and the recovery rate is dynamically adjusted based on the relationship between the delay mitigation level during the flight phase and flight duration, thereby improving the SIR model. On this basis, an analysis of the delay propagation between flight segments is conducted using the delay propagation network and the improved SIR model. The impact of delays in different segments on the entire air traffic is analyzed to identify key segments. Finally, this method is used to evaluate the importance of flight segments and to discover segments that have a significant impact on the generation and propagation of delays. A simulation experiment based on the actual operational data of the Central and Southern regional route network from January 1, 2022, to May 31, 2022, identified 12 flight segments, including HOK-LKO, AKUBA-LUMKO, LIG-OPUNI,among others,as significantly important compared to other segments. By comparing the results between traditional node importance evaluation algorithms, the current infectious disease model, and the improved infectious disease model, it was found that the improved infectious disease model can better identify segments that contribute more to the stability and connectivity of the route network, and the differences in importance of different segments within the entire air traffic network structure. This method is effective in improving the understanding and control of delay propagation.