Network Resilience and Rehabilitation Strategies for an Airport Movement Area Considering Traffic Flow and Road Class

Abstract

In this study, we propose an improved betweenness centrality (FDBC) algorithm to identify vulnerabilities in airport field operations, assist controllers in formulating emergency response strategies, and enhance the safety resilience of the maneuvering area network during external disturbances. The algorithm is developed by constructing a transportation network model for the airport movement area and extracting key nodes based on considerations of traffic flow and road class. Utilizing aircraft field operation rules, we define an assessment index for the average shortest path length of inbound and outbound activities. Comparative analyses of comprehensive resilience indexes under various recovery strategies are conducted to assess the network’s recovery ability (RA) and adaptability in the face of external disturbances. The goal is to identify the optimal recovery strategy that achieves a dynamic balance between development and safety. To validate our approach, we conducted an empirical study at an airport in southwest China, simulating the resilience of the airport movement area transportation network under varying road class coefficients, traffic flow weights, and road class weights. The results indicate that the airport movement area transportation network in the southwest region lacks small‐world and scale‐free network characteristics. The identification of important road intersections through the FDBC strategy proves to be more effective in discerning potential safety hazard orientations. Under the FDBC‐based recovery strategy, as traffic flow weights increase, the comprehensive resilience index of the network initially shows a smooth trend, followed by a decrease, then another period of smoothness before decreasing again. Increasing the road class coefficient can enhance the network’s recovery efficiency and resilience level, enabling the network to maintain a high level of recovery for an extended period. This is beneficial for enhancing the safety and stability of flight operations. However, in cases where traffic flow weights are high, the FDBC‐based recovery strategy, which solely considers traffic, exhibits a relatively slower network RA in response to degree‐valued perturbations. Overall, the traffic network in the airport movement area demonstrates the highest resilience under the FDBC‐based recovery strategy. It can rapidly transition the network from a failure state to a normal stable state, thereby improving emergency response efficiency and ensuring the safe operation of the traffic network in the airport movement area.