A multiobjective optimization approach for air traffic flow management for airspace safety enhancement
This work aims to enhance the safety of air traffic in a procedural airspace by air traffic flow management (ATFM) without compromizing air traffic demand. In civil aviation, collision risk is an important indicator for air traffic safety assessment. In this work, we propose a generic ATFM framework...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2022
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| Online Access: | https://hdl.handle.net/10356/159940 |
| _version_ | 1826121443625140224 |
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| author | Cai, Qing Ang, Haojie Alam, Sameer |
| author2 | School of Mechanical and Aerospace Engineering |
| author_facet | School of Mechanical and Aerospace Engineering Cai, Qing Ang, Haojie Alam, Sameer |
| author_sort | Cai, Qing |
| collection | NTU |
| description | This work aims to enhance the safety of air traffic in a procedural airspace by air traffic flow management (ATFM) without compromizing air traffic demand. In civil aviation, collision risk is an important indicator for air traffic safety assessment. In this work, we propose a generic ATFM framework based on multiobjective optimization for reducing lateral collision risk of the traffic in a given procedural airspace. The proposed framework aims to optimize the flight level assignment for a given set of flight plans such that the lateral collision risk can be reduced. To achieve this goal, we formulate an optimization problem containing two partially conflicting objective functions. We then adopt three well-known evolutionary algorithms, i.e., MODPSO, NSGA-II, and MOEA/D to solve the optimization problem. We specially design some of the operators of those al- gorithms to make them suitable for the optimization problem. We merge the solutions yielded by those three algorithms and filter out the final Pareto solutions. We carry out a case study on the procedural airspace of Singapore flight information region (FIR) with respect to twelve daily traffic data selected from the real traffic data for December 2019. Experiment results demonstrates that the lateral occupancy which is the key contributor to lateral risk can be reduced by 10.65% to 93.05% at a strategic planning level. This research contribute to strategic flight planning by assigning flight levels that may reduce the risk of collision in procedural airspace. |
| first_indexed | 2024-10-01T05:32:24Z |
| format | Conference Paper |
| id | ntu-10356/159940 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:32:24Z |
| publishDate | 2022 |
| record_format | dspace |
| spelling | ntu-10356/1599402022-09-24T23:30:21Z A multiobjective optimization approach for air traffic flow management for airspace safety enhancement Cai, Qing Ang, Haojie Alam, Sameer School of Mechanical and Aerospace Engineering 2022 IEEE Congress on Evolutionary Computation (CEC) Air Traffic Management Research Institute Engineering::Aeronautical engineering::Accidents and air safety Air Traffic Flow Management Collision Risk This work aims to enhance the safety of air traffic in a procedural airspace by air traffic flow management (ATFM) without compromizing air traffic demand. In civil aviation, collision risk is an important indicator for air traffic safety assessment. In this work, we propose a generic ATFM framework based on multiobjective optimization for reducing lateral collision risk of the traffic in a given procedural airspace. The proposed framework aims to optimize the flight level assignment for a given set of flight plans such that the lateral collision risk can be reduced. To achieve this goal, we formulate an optimization problem containing two partially conflicting objective functions. We then adopt three well-known evolutionary algorithms, i.e., MODPSO, NSGA-II, and MOEA/D to solve the optimization problem. We specially design some of the operators of those al- gorithms to make them suitable for the optimization problem. We merge the solutions yielded by those three algorithms and filter out the final Pareto solutions. We carry out a case study on the procedural airspace of Singapore flight information region (FIR) with respect to twelve daily traffic data selected from the real traffic data for December 2019. Experiment results demonstrates that the lateral occupancy which is the key contributor to lateral risk can be reduced by 10.65% to 93.05% at a strategic planning level. This research contribute to strategic flight planning by assigning flight levels that may reduce the risk of collision in procedural airspace. Civil Aviation Authority of Singapore (CAAS) National Research Foundation (NRF) Submitted/Accepted version This research is supported by the National Research Foundation, Singapore, and the Civil Aviation Authority of Singapore, under the Aviation Transformation Programme. 2022-09-19T01:03:56Z 2022-09-19T01:03:56Z 2022 Conference Paper Cai, Q., Ang, H. & Alam, S. (2022). A multiobjective optimization approach for air traffic flow management for airspace safety enhancement. 2022 IEEE Congress on Evolutionary Computation (CEC). https://dx.doi.org/10.1109/CEC55065.2022.9870355 978-1-6654-6708-7 https://hdl.handle.net/10356/159940 10.1109/CEC55065.2022.9870355 en © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/CEC55065.2022.9870355. application/pdf |
| spellingShingle | Engineering::Aeronautical engineering::Accidents and air safety Air Traffic Flow Management Collision Risk Cai, Qing Ang, Haojie Alam, Sameer A multiobjective optimization approach for air traffic flow management for airspace safety enhancement |
| title | A multiobjective optimization approach for air traffic flow management for airspace safety enhancement |
| title_full | A multiobjective optimization approach for air traffic flow management for airspace safety enhancement |
| title_fullStr | A multiobjective optimization approach for air traffic flow management for airspace safety enhancement |
| title_full_unstemmed | A multiobjective optimization approach for air traffic flow management for airspace safety enhancement |
| title_short | A multiobjective optimization approach for air traffic flow management for airspace safety enhancement |
| title_sort | multiobjective optimization approach for air traffic flow management for airspace safety enhancement |
| topic | Engineering::Aeronautical engineering::Accidents and air safety Air Traffic Flow Management Collision Risk |
| url | https://hdl.handle.net/10356/159940 |
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