In this paper we present a Genetic Algorithm designed to manage the mission of an UAS that has to visit a set of mission points into a congested airport TMA (Terminal Area) . The genetic approach is useful to model the presence of different avoidance options: populations of pilots that have different “avoidance philosophy” are crossed in order to obtain a good mix of avoidance technique. Our methodology is based on a strategic, intent-based, non-cooperative (only one aircraft – the UAV –maneuver), geometric (prediction is based on geometrical projections) and distributed (as opposed to centralized) approach. Finally, real piloted traffic data from the Milano Linate (LIML) Terminal Area are used to test the algorithm.
Airborne Conflict Modeling and Resolution for UAS Insertion in Civil Non-Segregated Airspace / Persiani C.A.; Bagassi S.. - STAMPA. - (2010), pp. 123-132. (Intervento presentato al convegno EIWAC 2010 - ENRI's International Workshop on ATM/CNS tenutosi a Tokyo Japan nel 10-12 November 2010).
Airborne Conflict Modeling and Resolution for UAS Insertion in Civil Non-Segregated Airspace
PERSIANI, CARLO ALFREDO;BAGASSI, SARA
2010
Abstract
In this paper we present a Genetic Algorithm designed to manage the mission of an UAS that has to visit a set of mission points into a congested airport TMA (Terminal Area) . The genetic approach is useful to model the presence of different avoidance options: populations of pilots that have different “avoidance philosophy” are crossed in order to obtain a good mix of avoidance technique. Our methodology is based on a strategic, intent-based, non-cooperative (only one aircraft – the UAV –maneuver), geometric (prediction is based on geometrical projections) and distributed (as opposed to centralized) approach. Finally, real piloted traffic data from the Milano Linate (LIML) Terminal Area are used to test the algorithm.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
