A fuzzy modeling approach to optimize control and decision making in conflict management in air traffic control. (January 2018)

• Record Type: Journal Article
• Authors: Volpe Lovato, Agnaldo; Hora Fontes, Cristiano; Embiruçu, Marcelo; Kalid, Ricardo
• Is Part Of: Computers & industrial engineering. Volume 115(2018)
• Page Start: 167
• Page End: 189
• Publication Date: 2018-01
• Subjects: Fuzzy logic -- Air traffic control -- Support decision-making -- Optimization -- Safety; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2017.11.008
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: Novel approach for the control of conflict in the air traffic route. The proposed strategy enables smoother and efficient adjustments in the aircraft speed. The potential of the proposed strategy is demonstrated by the faster elimination of the conflicts. The proposed approach is able to detect and remove longitudinal conflicts in advance. The approach provides a potential tool to support decision-making and to improve the use of airspace. Abstract: The intensification of air traffic worldwide has increased the complexity of the control operations and the search for alternatives to support decision-making in this sector. This paper presents two fuzzy models, structured according to Mamdani, for the control of conflict in the air traffic route, based on the manipulation of the longitudinal speed of the aircraft, considering the rules set out by the International Civil Aviation Organization (ICAO). Both fuzzy models work jointly following a dynamic approach. The first model proposes a metric to quantify the longitudinal conflict levels between two aircraft in the same direction (located in the same airway) and the second model provides the longitudinal acceleration of the aircraft based on the level of conflict detected. The results show that the proposed approach is able to detect and remove longitudinal conflicts in advance, providing a potential tool to support decision-making and to improve the safety and the optimized use of airspace.