A complexity reduction approach to the detection of safety critical situations in Air Traffic Management systems

In Air Traffic Management (ATM) systems, catastrophic events are often caused by errors made by agents operating in the procedures. Detecting safety critical situations that may arise in the evolution of ATM systems is of primary importance in the analysis of their behavior. The inherent complexity of ATM systems, typically involving a large number of agents, makes this analysis prohibitive today. Compositionality has been an effective way of tackling this problem. We present a compositional hybrid systems framework to accurately describe the behavior of the agents operating in ATM scenarios and of their interaction. We then expose some results that reduce the computational effort required in detecting safety critical situations. Benefits from the use of this complexity reduction approach are illustrated using the analysis of the Airborne Separation-In Trail Procedure (ASEP-ITP).