|Title||An Empirically grounded Agent Based simulator for Air Traffic Management in the SESAR scenario|
|Authors||Gurtner, G., Bongiorno, C., Ducci, M. and Miccichè, S.|
In this paper we present a simulator allowing to perform policy experiments relative to the air traffic management. Different SESAR solutions can be implemented in the model to see the reaction of the different stakeholders as well as other relevant metrics (delay, safety, etc). The model describes both the strategic phase associated to the planning of the flight trajectories and the tactical modifications occurring in the en-route phase. An implementation of the model is available as an open-source software and is freely accessible by any user.
More specifically, different procedures related to business trajectories and free-routing are tested and we illustrate the capabilities of the model on an airspace which implements these concepts. After performing numerical simulations with the model, we show that in a free-routing scenario the controllers perform less operations but the conflicts are dispersed over a larger portion of the airspace. This can potentially increase the complexity of conflict detection and resolution for controllers.
In order to investigate this specific aspect, we consider some metrics used to measure traffic complexity. We first show that in non-free-routing situations our simulator deals with complexity in a way similar to what humans would do. This allows us to be confident that the results of our numerical simulations relative to the free-routing can reasonably forecast how human controllers would behave in this new situation. Specifically, our numerical simulations show that most of the complexity metrics decrease with free-routing, while the few metrics which increase are all linked to the flight level changes. This is a non-trivial result since intuitively the complexity should increase with free-routing because of problematic geometries and more dispersed conflicts over the airspace.
|Keywords||Air Traffic Simulator; Agent-Based Model; ABM; Air Traffic Management; ATM; airspace complexity; free-routing|
|Journal||Journal of Air Transport Management|
|Journal citation||59, pp. 26-43|
|Accepted author manuscript||paper_air_traffic_simulator_for_publication_edited.pdf|
|Digital Object Identifier (DOI)||doi:10.1016/j.jairtraman.2016.11.004|
|Published in print||Mar 2017|
|Published online||29 Nov 2016|
|Published||29 Nov 2016|