Complex System Approach in Modeling Airspace Congestion Dynamics

The dynamical behaviour of groups of airspace sectors, e.g. Functional Airspace Blocks, is not trivial to be analysed without appropriate theoretical tools. In this paper, we suggest a discrete model based on cellular automata and multi agent systems to express the congestion dynamics and complexity in the controlled airspace. Discrete time simulations have been performed with random selected scenarios of traffic and with independent sector parameters to investigate the impact of availability of local sectors on the whole state of the airspace. Obtained results show the existence of a traffic threshold that leads to a theoretical saturation of airspace. The test scenario showed a phase transition phenomenon towards the congestion of the European airspace at the resulting traffic threshold circa 50 000 flights. Validation using real data shows the predictive abilities of the model.