A Hybrid Approach for Detecting and Resolving Conflicts in Air Traffic Routes
This paper presents a hybrid model for the detection and resolution of conflicts in air traffic routes involving flight level change actions and adjustment of the longitudinal acceleration of aircraft. The strategy comprises an integrated approach that uses a fuzzy model to quantify the level of lon...
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2019-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8908739/ |
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doaj-a8b937ddb8e64031a8b0bb8e2f7408ba2021-03-30T00:27:14ZengIEEEIEEE Access2169-35362019-01-01716986516988710.1109/ACCESS.2019.29549768908739A Hybrid Approach for Detecting and Resolving Conflicts in Air Traffic RoutesAgnaldo V. Lovato0https://orcid.org/0000-0003-3798-2864Cristiano H. Fontes1https://orcid.org/0000-0001-8020-6815Marcelo Embirucu2https://orcid.org/0000-0002-8453-1014Ricardo Kalid3https://orcid.org/0000-0001-9265-5263Department of Science and Technology, State University of Southwest Bahia, Jequié, BrazilPrograma de Engenharia Industrial, Escola Politécnica, Universidade Federal da Bahia, Salvador, BrazilPrograma de Engenharia Industrial, Escola Politécnica, Universidade Federal da Bahia, Salvador, BrazilPrograma de Engenharia Industrial, Escola Politécnica, Universidade Federal da Bahia, Salvador, BrazilThis paper presents a hybrid model for the detection and resolution of conflicts in air traffic routes involving flight level change actions and adjustment of the longitudinal acceleration of aircraft. The strategy comprises an integrated approach that uses a fuzzy model to quantify the level of longitudinal conflict between two aircraft on the same airway. In addition, optimum flight level change actions between aircraft are calculated through a global and dynamic analysis involving the recognition of clusters of aircraft in conflict and the search for the best scenario by means of a genetic algorithm that minimizes the sum of positive conflicts. 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, improve safety and optimize the use of airspace.https://ieeexplore.ieee.org/document/8908739/Air traffic controlfuzzy logicgenetic algorithmoptimizationclustering algorithmsupport decision-making |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Agnaldo V. Lovato Cristiano H. Fontes Marcelo Embirucu Ricardo Kalid |
| spellingShingle |
Agnaldo V. Lovato Cristiano H. Fontes Marcelo Embirucu Ricardo Kalid A Hybrid Approach for Detecting and Resolving Conflicts in Air Traffic Routes IEEE Access Air traffic control fuzzy logic genetic algorithm optimization clustering algorithm support decision-making |
| author_facet |
Agnaldo V. Lovato Cristiano H. Fontes Marcelo Embirucu Ricardo Kalid |
| author_sort |
Agnaldo V. Lovato |
| title |
A Hybrid Approach for Detecting and Resolving Conflicts in Air Traffic Routes |
| title_short |
A Hybrid Approach for Detecting and Resolving Conflicts in Air Traffic Routes |
| title_full |
A Hybrid Approach for Detecting and Resolving Conflicts in Air Traffic Routes |
| title_fullStr |
A Hybrid Approach for Detecting and Resolving Conflicts in Air Traffic Routes |
| title_full_unstemmed |
A Hybrid Approach for Detecting and Resolving Conflicts in Air Traffic Routes |
| title_sort |
hybrid approach for detecting and resolving conflicts in air traffic routes |
| publisher |
IEEE |
| series |
IEEE Access |
| issn |
2169-3536 |
| publishDate |
2019-01-01 |
| description |
This paper presents a hybrid model for the detection and resolution of conflicts in air traffic routes involving flight level change actions and adjustment of the longitudinal acceleration of aircraft. The strategy comprises an integrated approach that uses a fuzzy model to quantify the level of longitudinal conflict between two aircraft on the same airway. In addition, optimum flight level change actions between aircraft are calculated through a global and dynamic analysis involving the recognition of clusters of aircraft in conflict and the search for the best scenario by means of a genetic algorithm that minimizes the sum of positive conflicts. 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, improve safety and optimize the use of airspace. |
| topic |
Air traffic control fuzzy logic genetic algorithm optimization clustering algorithm support decision-making |
| url |
https://ieeexplore.ieee.org/document/8908739/ |
| work_keys_str_mv |
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