Speed control strategies for E-AMAN using holding detection-delay prediction model

Abstract

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.