2019 Fiscal Year Annual Research Report
Synergistic ground holding algorithm based on real-time air traffic pattern classification and off-line buffer optimization
| Project/Area Number |
19K21092
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| Allocation Type | Multi-year Fund |
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| Research Institution | Japan Aerospace EXploration Agency |
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Principal Investigator |
アンドレエバ森 アドリアナ 国立研究開発法人宇宙航空研究開発機構, 航空技術部門, 研究開発員 (30747499)
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| Project Period (FY) |
2019-04-01 – 2020-03-31
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| Keywords | ground holding / airborne delay / capacity loss / traffic pattern / machine learning |
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| Outline of Annual Research Achievements |
This research develops a novel synergistic ground holding algorithm based on real-time air traffic pattern classification and off-line buffer optimization. When the expected airborne holding time will exceed a certain constant buffer value, this excess waiting is set as ground holding, i.e. aircraft are kept on the ground before departure. In our research, we consider various real-world uncertainties to determine the optimal buffer applied by the ground holding program. We then build a simulated database and develop a machine-learning-based traffic pattern classifier which, based on traffic features, predicts the optimal ground holding control parameters and potential savings within mean absolute percentage error of 17.96% of the potential optimal ones.
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