Current students

Eline Bakker (TU Delft) – Design and Evaluation of a Visual Interface for an En-Route Air Traffic Control Merging Task

In the past decades, the air traffic growth has resulted in increasingly complex situations involving more aircraft simultaneously. In order to guarantee safety is maintained within the increasingly crowded airspace, new solutions are expected. In collaboration with the LVNL, an Inbound Traffic Support System interface was developed. The goal of the interface is to visualize the possible solutions of an area controller’s task of merging aircraft towards a restricted waypoint in the current work domain, such that the impact of decisions made can be foreseen.  By showing the affordances of the work domain, the display keeps the air traffic controller as the active decision maker rather than issuing advisories.


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.