Speed control strategies for E-AMAN using holding detection-delay prediction model
Reducing flight delays is considered one of the biggest challenges of the air transportation system due to its far-reaching economic, operational, and environmental impact. Airlines and Air Navigation Service Providers (ANSPs) must collaborate to optimize their procedures in order to manage delays....
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sg-ntu-dr.10356-1465382021-02-27T20:10:22Z Speed control strategies for E-AMAN using holding detection-delay prediction model Dhief, Imen Lim, Zhi Jun Goh, Sim Kuan Pham, Duc-Thinh Alam, Sameer Schultz, Michael School of Mechanical and Aerospace Engineering 10th SESAR Innovation Days Air Traffic Management Research Institute Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Engineering::Aeronautical engineering::Aviation Extended AMAN Speed Control Reducing flight delays is considered one of the biggest challenges of the air transportation system due to its far-reaching economic, operational, and environmental impact. Airlines and Air Navigation Service Providers (ANSPs) must collaborate to optimize their procedures in order to manage delays. The SESAR Solution, Extended Arrivals Manager (E-AMAN), allows for early sequencing of the flights, thereby reducing the aircraft holding times and thus managing congestion in Terminal Maneuver Airspace (TMA). However, there is a lack of methodological approaches for transferring the flight delays and holdings from the approach phase to the cruise phase. To this end, we have approached this problem using both data-driven and optimization techniques. First, we propose a method to detect the holding pattern/time from historical trajectory data. Then a prediction model is introduced to predict holdings and delays 200NM from the airport. Finally, we develop an optimization model that takes the predicted delays as an input and provides the airlines/ANSPs with adequate speed adjustment, which can absorb delays in the approach phase and transfer them to the cruise phase. Results demonstrate that better prediction of holding pattern/time can lead to predicting the flight delays, in the approach phase, with high accuracy. Furthermore, the proposed speed control model shows that, with a speed reduction of less than 10% at 500NM from the airport, up to 70% of the initial delays could be absorbed in the cruise phase. As a result, the average delay per flight (at the approach phase) is decreased from 6 minutes to almost 2 minutes. Civil Aviation Authority of Singapore (CAAS) National Research Foundation (NRF) Accepted version This research is supported by the National Research Foundation, Singapore, and the Civil Aviation Authority of Singapore, under the Aviation Transformation Programme. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not reflect the views of National Research Foundation, Singapore and the Civil Aviation Authority of Singapore. 2021-02-25T06:11:24Z 2021-02-25T06:11:24Z 2020 Conference Paper Dhief, I., Lim, Z. J., Goh, S. K., Pham, D.-T., Alam, S., & Schultz, M. (2020). Speed control strategies for E-AMAN using holding detection-delay prediction model. Proceedings of 10th SESAR Innovation Days. https://hdl.handle.net/10356/146538 en © 2021 SESARJU. All rights reserved. application/pdf |
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Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Engineering::Aeronautical engineering::Aviation Extended AMAN Speed Control |
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Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Engineering::Aeronautical engineering::Aviation Extended AMAN Speed Control Dhief, Imen Lim, Zhi Jun Goh, Sim Kuan Pham, Duc-Thinh Alam, Sameer Schultz, Michael Speed control strategies for E-AMAN using holding detection-delay prediction model |
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Reducing flight delays is considered one of the biggest challenges of the air transportation system due to its far-reaching economic, operational, and environmental impact. Airlines and Air Navigation Service Providers (ANSPs) must collaborate to optimize their procedures in order to manage delays. The SESAR Solution, Extended Arrivals Manager (E-AMAN), allows for early sequencing of the flights, thereby reducing the aircraft holding times and thus managing congestion in Terminal Maneuver Airspace (TMA). However, there is a lack of methodological approaches for transferring the flight delays and holdings from the approach phase to the cruise phase. To this end, we have approached this problem using both data-driven and optimization techniques. First, we propose a method to detect the holding pattern/time from historical trajectory data. Then a prediction model is introduced to predict holdings and delays 200NM from the airport. Finally, we develop an optimization model that takes the predicted delays as an input and provides the airlines/ANSPs with adequate speed adjustment, which can absorb delays in the approach phase and transfer them to the cruise phase. Results demonstrate that better prediction of holding pattern/time can lead to predicting the flight delays, in the approach phase, with high accuracy. Furthermore, the proposed speed control model shows that, with a speed reduction of less than 10% at 500NM from the airport, up to 70% of the initial delays could be absorbed in the cruise phase. As a result, the average delay per flight (at the approach phase) is decreased from 6 minutes to almost 2 minutes. |
author2 |
School of Mechanical and Aerospace Engineering |
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School of Mechanical and Aerospace Engineering Dhief, Imen Lim, Zhi Jun Goh, Sim Kuan Pham, Duc-Thinh Alam, Sameer Schultz, Michael |
format |
Conference or Workshop Item |
author |
Dhief, Imen Lim, Zhi Jun Goh, Sim Kuan Pham, Duc-Thinh Alam, Sameer Schultz, Michael |
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Dhief, Imen |
title |
Speed control strategies for E-AMAN using holding detection-delay prediction model |
title_short |
Speed control strategies for E-AMAN using holding detection-delay prediction model |
title_full |
Speed control strategies for E-AMAN using holding detection-delay prediction model |
title_fullStr |
Speed control strategies for E-AMAN using holding detection-delay prediction model |
title_full_unstemmed |
Speed control strategies for E-AMAN using holding detection-delay prediction model |
title_sort |
speed control strategies for e-aman using holding detection-delay prediction model |
publishDate |
2021 |
url |
https://hdl.handle.net/10356/146538 |
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1696984345004212224 |