The work that is presented in this paper is part of an ongoing study on the relationship between airspace structure and capacity. The present paper investigates the degree of structuring needed to maximize capacity for decentralized en-route airspace. To this end, four decentralized en-route airspace concepts, which vary in terms of the number of constrained degrees of freedom, were compared using fast-time simulations, for both nominal and non-nominal conditions. The airspace structure-capacity relationship was studied from the effect of multiple traffic demand densities on airspace metrics. The results indicated that structuring methods that over-constrained the horizontal path of aircraft reduced capacity, as traffic demand displays no predominant patterns in the horizontal dimension for decentralization. The results also showed that capacity was maximized when a vertical segmentation of airspace was used to separate traffic with different travel directions at different flight levels. This mode of structuring improved performance over completely unstructured airspace by reducing relative velocities between aircraft cruising at the same altitude, while allowing direct horizontal routes.

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The most relevant SESAR 2020 solutions dealing with future Capacity Management processes are Dynamic Airspace Configuration (DAC) and Flight Centric ATC (FCA). Both concepts, DAC and FCA, rely on traffic flow complexity assessment. For this reason, complexity assessments processes, methods and metrics, become one of the main constraints to deal with the growing demand and increasing airspace capacity. The aim of this work is to identify the influence of trajectories’ uncertainty in the quality of the predictions of complexity of traffic demand and the effectiveness of Demand Capacity Balance (DCB) airspace management processes, in order to overcome the limitations of existing complexity assessment approaches to support Capacity Management processes in a Trajectory-Based Operations (TBO) environment. This paper presents research conducted within COTTON project, sponsored by the SESAR Joint Undertaking and EU’s Horizon 2020 research and innovation program. The main objective is to deliver innovative solutions to maximize the performance of the Capacity Management procedures based on information in a TBO environment.