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Complexity Management Using Metrics for Trajectory Flexibility Preservation and Constraint Minimization
Author(s) -
Husni Idris,
Nola Shen,
David J. Wing
Publication year - 2011
Publication title -
11th aiaa aviation technology, integration, and operations (atio) conference
Language(s) - English
Resource type - Conference proceedings
DOI - 10.2514/6.2011-6809
Subject(s) - flexibility (engineering) , computer science , minification , trajectory , constraint (computer aided design) , mathematical optimization , computational complexity theory , algorithm , mathematics , statistics , physics , astronomy , programming language , geometry
The growing demand for air travel is increasing the need for mitigating air traffic congestion and complexity problems, which are already at high levels. At the same time new surveillance, navigation, and communication technologies are enabling major transformations in the air traffic management system, including net-based information sharing and collaboration, performance-based access to airspace resources, and trajectorybased rather than clearance-based operations. The new system will feature different schemes for allocating tasks and responsibilities between the ground and airborne agents and between the human and automation, with potential capacity and cost benefits. Therefore, complexity management requires new metrics and methods that can support these new schemes. This paper presents metrics and methods for preserving trajectory flexibility that have been proposed to support a trajectory-based approach for complexity management by airborne or ground-based systems. It presents extensions to these metrics as well as to the initial research conducted to investigate the hypothesis that using these metrics to guide user and service provider actions will naturally mitigate traffic complexity. The analysis showed promising results in that: (1) Trajectory flexibility preservation mitigated traffic complexity as indicated by inducing self-organization in the traffic patterns and lowering traffic complexity indicators such as dynamic density and traffic entropy. (2) Trajectory flexibility preservation reduced the potential for secondary conflicts in separation assurance. (3) Trajectory flexibility metrics showed potential application to support user and service provider negotiations for minimizing the constraints imposed on trajectories without jeopardizing their objectives.

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