Sensitivity analysis of conflict-free resolutions for the airborne cluster–ecosystem

Marko Radanovic, Miquel Angel Piera Eroles, Thimjo Koca

Research output: Contribution to journalArticle (Academic Journal)peer-review

3 Citations (Scopus)


To support the future automation of air traffic management, this study examines a decrement in the number of feasible, conflict-free avoidance maneuvers within a tactical air traffic system, relying on the concept of an airborne ecosystem. An ecosystem represents a set of aircraft with the trajectory-amendment, decision-making capability, whose trajectories are identified inside a computed airspace volume and causally involved in a safety event that is predicted for a certain look-ahead time from their current positions. The concept is based on the predicted conflict between two aircraft, whose trajectory segments are used for detection of the surrounding aircraft by identification of the spatiotemporal interdependencies. The potential resolution capacity is characterized by a decreasing rate of the feasible solutions over time, while the aircraft are flying toward the closest point of approach. Causal analysis was performed via the initialization of different cluster–ecosystem transitions with the goal of measuring the scenarios complexity in terms of the time-based conflict-free solutions, in front of the elapsed time to the aircraft collision. Simulation of eight ecosystems generated from two pairwise conflicts with different avoidance capacities illustrates a potential of negotiation as the aircraft tendency to reach a resolution agreement via early or late decisions.

Original languageEnglish
Pages (from-to)37-48
Number of pages12
JournalJournal of Air Transportation
Issue number1
Publication statusPublished - 2018

Bibliographical note

Funding Information:
This research is partially supported by the Horizon 2020 Research and Innovation Programme project Adaptive Self-Governed Aerial Ecosystem by Negotiated Traffic (grant agreement number 699313) and the national Spanish project Automated Air Traffic Management for RPAS (reference TRA2017-88724-R). Opinions expressed in this paper reflect the authors’ views only.

Publisher Copyright:
© 2018 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

Copyright 2020 Elsevier B.V., All rights reserved.


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