Evaluating ground–air network vulnerabilities in an integrated terminal maneuvering area using co-evolutionary computational red teaming

The inherent complexity of a terminal maneuvering area (TMA) necessitates a system-level analysis to understand the overall system risk and vulnerabilities. The performance of advanced air traffic control (ATC) procedures, such as dynamic Continuous Descent Approaches (CDAs), may not be appropriately assessed without considering the complex interactions among other parts of the environment and the context in which they operate. The focus of this paper is a TMA system which integrates arrival and departure operations. It combines air and ground side resources to model and understand system-level vulnerabilities.We propose a methodology using the Computational Red Teaming (CRT) framework to identify ground–air network bottlenecks by exploring areas of vulnerability in the integrated TMA. The search engine in CRT relies on co-evolutionary search which evolves reciprocal interaction of traffic distributions and ground events (including runways, taxiways and gates). These interactions are modeled to identify inefficiencies resultant from the integration of arrival and departure operations. By evaluating these interactions, we are also able to identify “improvement opportunities” in the implementation of future air traffic management (ATM) concepts and, thereby, understand and work-around major bottlenecks which cause system inefficiencies. We illustrate the methodology on the Sydney Kingsford-Smith Airport’s domestic terminal area using a dynamic CDA scenario. Among our findings, taxiway B can cause significant delays if it is impacted by a ground event. In general, taxiways have been found to be a critical airport component with interactions between arrivals and departures, significantly impacting the airport’s throughput capacity.

► A co-evolutionary computational red teaming was developed.
► Different computational experiments were designed and implemented.
► The results showed that dynamic CDA can improve TMA system’s throughput capacity.
► Our analysis identified the bottlenecks of the integrated TMA system.
► Our analysis synthesize an overall situational awareness picture that decision makers can use.