Optimization-Based Autonomous Air Traffic Control for Airspace Capacity Improvement
In order to handle increasing demand in air transportation, high-level automation support seems inevitable. This article presents an optimization-based autonomous air traffic control (ATC) system and the determination of airspace capacity with respect to the proposed system. We model aircraft dynami...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Institute of Electrical and Electronics Engineers (IEEE)
2021
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| Online Access: | https://hdl.handle.net/1721.1/130406 |
| _version_ | 1811073879390552064 |
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| author | Baspinar, Baris Koyuncu, Emre |
| author2 | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics |
| author_facet | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics Baspinar, Baris Koyuncu, Emre |
| author_sort | Baspinar, Baris |
| collection | MIT |
| description | In order to handle increasing demand in air transportation, high-level automation support seems inevitable. This article presents an optimization-based autonomous air traffic control (ATC) system and the determination of airspace capacity with respect to the proposed system. We model aircraft dynamics and guidance procedures for simulation of aircraft motion and trajectory prediction. The predicted trajectories are used during decision process and simulation of aircraft motion is the key factor to create a traffic environment for estimation of airspace capacity. We define the interventions of an air traffic controller (ATCo) as a set of maneuvers that is appropriate for real air traffic operations. The decision process of the designed ATC system is based on integer linear programming (ILP) constructed via a mapping process that contains discretization of the airspace with predicted trajectories to improve the time performance of conflict detection and resolution. We also present a procedure to estimate the airspace capacity with the proposed ATC system. This procedure consists of constructing a stochastic traffic simulation environment that includes the structure of the evaluated airspace. The approach is validated on real air traffic data for enroute airspace, and it is also shown that the designed ATC system can manage traffic much denser than current traffic. |
| first_indexed | 2024-09-23T09:39:36Z |
| format | Article |
| id | mit-1721.1/130406 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T09:39:36Z |
| publishDate | 2021 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | mit-1721.1/1304062022-09-26T12:55:15Z Optimization-Based Autonomous Air Traffic Control for Airspace Capacity Improvement Baspinar, Baris Koyuncu, Emre Massachusetts Institute of Technology. Department of Aeronautics and Astronautics In order to handle increasing demand in air transportation, high-level automation support seems inevitable. This article presents an optimization-based autonomous air traffic control (ATC) system and the determination of airspace capacity with respect to the proposed system. We model aircraft dynamics and guidance procedures for simulation of aircraft motion and trajectory prediction. The predicted trajectories are used during decision process and simulation of aircraft motion is the key factor to create a traffic environment for estimation of airspace capacity. We define the interventions of an air traffic controller (ATCo) as a set of maneuvers that is appropriate for real air traffic operations. The decision process of the designed ATC system is based on integer linear programming (ILP) constructed via a mapping process that contains discretization of the airspace with predicted trajectories to improve the time performance of conflict detection and resolution. We also present a procedure to estimate the airspace capacity with the proposed ATC system. This procedure consists of constructing a stochastic traffic simulation environment that includes the structure of the evaluated airspace. The approach is validated on real air traffic data for enroute airspace, and it is also shown that the designed ATC system can manage traffic much denser than current traffic. 2021-04-08T11:19:16Z 2021-04-08T11:19:16Z 2020-12 2021-04-07T16:41:54Z Article http://purl.org/eprint/type/JournalArticle 0018-9251 https://hdl.handle.net/1721.1/130406 Bas ̧pın, Barıs ̧ et al. “Optimization-Based Autonomous Air Traffic Control for Airspace Capacity Improvement.” IEEE Transactions on Aerospace and Electronic Systems, 56, 6 (December 2020): 4814 - 4830 © 2020 The Author(s) en 10.1109/TAES.2020.3003106 IEEE Transactions on Aerospace and Electronic Systems Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Institute of Electrical and Electronics Engineers (IEEE) MIT web domain |
| spellingShingle | Baspinar, Baris Koyuncu, Emre Optimization-Based Autonomous Air Traffic Control for Airspace Capacity Improvement |
| title | Optimization-Based Autonomous Air Traffic Control for Airspace Capacity Improvement |
| title_full | Optimization-Based Autonomous Air Traffic Control for Airspace Capacity Improvement |
| title_fullStr | Optimization-Based Autonomous Air Traffic Control for Airspace Capacity Improvement |
| title_full_unstemmed | Optimization-Based Autonomous Air Traffic Control for Airspace Capacity Improvement |
| title_short | Optimization-Based Autonomous Air Traffic Control for Airspace Capacity Improvement |
| title_sort | optimization based autonomous air traffic control for airspace capacity improvement |
| url | https://hdl.handle.net/1721.1/130406 |
| work_keys_str_mv | AT baspinarbaris optimizationbasedautonomousairtrafficcontrolforairspacecapacityimprovement AT koyuncuemre optimizationbasedautonomousairtrafficcontrolforairspacecapacityimprovement |