NASA has developed the Autonomous Operations Planner (AOP) airborne decision support tool to explore advanced air traffic control concepts that include delegating separation authority to aircraft. A key element of the AOP is its strategic conflict resolution (CR) algorithm, which must resolve conflicts while maintaining conformance with traffic flow management constraints. While a previous CR algorithm, which focused on broader flight plan optimization objectives as a part of conflict resolution, had successfully been developed, new research has identified the need for resolution routes the users find more acceptable (i.e., simpler and more intuitive). A new CR algorithm is presented that uses a combination of pattern-based maneuvers and a genetic algorithm to achieve these new objectives. Several lateral and vertical maneuver patterns are defined and the application of the genetic algorithm explained. A new approach to defining a conflicted fitness function using estimates of the local conflict region around a conflicted trajectory is also presented. Preliminary performance characteristics of the implemented algorithm are provided.
Pattern-Based Genetic Algorithm for Airborne Conflict Resolution
AIAA Guidance, Navigation, and Control Conference and Exhibit ; 2006 ; Keystone, CO, United States
2006-08-21
Aufsatz (Konferenz)
Keine Angabe
Englisch
AIAA-2006-6060 Pattern-Based Genetic Algorithm for Airborne Conflict Resolution
British Library Conference Proceedings | 2006
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