To support future automated transitions among the ATM safety nets, this study elaborates identification of the complex traffic scenarios based on the concept of aerial ecosystems. As an extension of the TCAS operational domain and evolving from the separation management towards collision avoidance layer, the concept has been developed as a stepwise algorithm for identification of cooperative aircraft involved in the safety event – detected conflict, and negotiating their resolution trajectories before the ecosystem deadlock event occurs, in which at least one aircraft stays out of a conflict-free resolution. As a response to this threshold, the paper examines generation of both acceptable and candidate resolution trajectories, with respect to the original aircraft trajectories. The candidate trajectories are generated from a set of tactical waypoints and a return waypoint to the original trajectory. Described methodology has been practically implemented to one ecosystem scenario, characterizing its evolution in terms of the intrinsic complexity. By introducing the heading maneuver changes and delay in the resolution process, the results have shown how the scenario complexity is increasing, especially affected by the states of two aircraft in the initial conflict. Furthermore, it has been demonstrated an evolution in the amount of the acceptable and candidate trajectory solutions, for which the minimum complexity value is satisfied. A goal of the study was to explore the lateral resolutions capacity at certain moments and its timely decrement.
|Title of host publication||Identification of Spatiotemporal Interdependencies and Complexity Evolution in a Multiple Aircraft Environment|
|Publication status||Published - 2017|
|Event||7th SESAR Innovation Days, SIDs 2017 - Belgrade, Serbia|
Duration: 28 Nov 2017 → 30 Nov 2017
|Name||SESAR Innovation Days|
|Conference||7th SESAR Innovation Days, SIDs 2017|
|Period||28/11/17 → 30/11/17|
Bibliographical noteFunding Information:
ACKNOWLEDGMENT This research is partially supported by the H2020 Research and Innovation Programme, the project: “Adaptive self-Governed aerial Ecosystem by Negotiated Traffic” (Grant Agreement No. 699313). Opinions reflect the authors’ views only.
© 2017, SESAR Joint Undertaking. All rights reserved.
Copyright 2020 Elsevier B.V., All rights reserved.
- Aircraft manoueverability
- Candidate resolution trajectories
- Ecosystem identification
- Spatiotemporal interdependencies