Matthijs Ottenhoff (TU Delft) – Wind and Trajectory Uncertainty in a 4D Trajectory Management Interface
With air traffic numbers increasing, a shift in the Air Traffic Management system towards 4D flight plans, where an aircraft trajectory is pre-planned in both time and space, is foreseen. When these pre-planned trajectories are subsequently executed, unforeseen airspace perturbations, such as weather, sequencing and changing airspace constraints, will inevitably require small changes in the trajectories to be made by the air traffic controller. This perturbation management control task will consist of ensuring a safe airspace while adhering to the strict time constraints imposed by the 4D flight plan. In collaboration with LVNL, a decision support interface was designed and evaluated with the aim of visualizing possible conflict resolutions in the 4D domain. A special focus was put on the integration of wind and trajectory uncertainty information into the interface.
Christophe Vakaet (TU Delft) – development of a Dynamic Taxi-time system
Ground control uses the Departure Sequence Planner (DSP) to optimally plan departures within the operational constraints. The DSP uses an estimated Variable Taxi Time (VTT) to calculate an aircraft’s Target Take-Off Time (TTOT). If the VTT is underestimated flights will not make the determined TTOT, while an overestimation requires the air traffic controller to tactically hold an aircraft. These consequences result in delays, capacity losses, additional workload, and uncertainty. This uncertainty inhibits further operational optimizations. The VTT is currently predicted based on the average taxi times for different gate-runway combinations, wake turbulence categories, deicing procedure, and simplified runway configuration. The goal of this project is to improve VTT predictions by employing machine learning techniques and additional data sources such as traffic density, weather, aircraft type, and more.
Robin Vervaat (TU Delft) – Priority-based flight scheduling in the tactical phase
Years of growth in air travel have meant that, as usage is nearing current capacity, delays are becoming virtually inevitable for air carriers operating in our airspace. Flight delays have a significant impact on airport and airline operations, as well as their cost. As such, tactical planning of the flights has become increasingly important, especially for a hub-operator with many connecting passengers. In collaboration with LVNL, KLM and Amsterdam Airport Schiphol, a novel model is being investigated tasked with the Arrival Sequencing and Scheduling of flights considering (airline) priority criteria. Smarter use is to be made of the available infrastructure in order to increase capacity and decrease delay (costs), however, fairness and equality between stakeholders will still need to be upheld.
Thijs Scheffers (Hogeschool van Amsterdam) – Validating air traffic systems of the LVNL in the arrival process
Since 13 November 2018, there has been a new arrival manager system at Schiphol in use, called ASAP. It replaces the old arrival system, called Inbound Planning (IBP). LVNL has got two systems to determine the estimated landing time (ELDT), called ASAP and AAA. They start determining the ELDT for all inbound flights approximately 3 hours before expected landing. The ELDTs generated by AAA are send to the Central Information System Schiphol (CISS) of Schiphol. However, the ELDTs generated by ASAP are only used internally by the LVNL. Therefore, due to the change on the input data set source and the moment of reception, a comparative analysis is needed understand the quality of each data set, the predictability and its benefits of use for calculating the ELDT on a more accurate manner.
Max (TU Delft) – Aircraft noise model validation using noise measurment feedback
One of the current factors limiting the growth of the aviation industry in the Netherlands is the relationship between the aviation sector and local communities around airports. Aircraft noise production is one of the main causes of nuisance in residential areas reported by RIVM. It is therefore, for the aviation industry as a whole, of great importance to gain a better understanding of the methodology of aircraft noise modelling and make improvements on this modelling process if deficiencies in the current model are detected. The validation of the aircraft noise model, using noise measurements taken around the airport, is crucial for the scientific foundation of the model. This scientific foundation is expected to increase the transparency in how noise calculations are performed, which increases community trust in the aviation industry as a whole.