Current students

Edzer Oosterhof (MSc)Analysis and Optimization of Air Traffic Bunching for the Area Control Center

With the current growth in air traffic and the resulting developments in terms of environmental issues and noise abatement, the pressure on the Area Control Center (ACC) is growing. On the one hand the Terminal Control Area (TMA) requires arriving traffic to be handed over accurately sequenced and merged, and on the other hand the ACC tries to minimize the miles flown in its sector. At the tactical level, there are Air Traffic Flow Management (ATFM) measures in place for traffic within Europe. However, no such tactical measures exist for traffic from the North Atlantic Tracks, increasing the probability that bunching occurs in the ACC during peak loads. By tactically predicting bunching in the sector and at the Initial Approach Fixes, a concept for debunching should be devised that focusses on airborne delay consumption and sequencing of traffic in the Upper control Areas (UTA) before it enters the Control Area (ACC), decreasing the pressure on the ACC.


Stephanie Wiechers (MSc) – Visual Interface to Support Improved EAT Adherence at IAF when Holding

As Schiphol is one of the busiest airport in the world, with tight flight schedules and urban areas that lie under arrival routes, adherence to the time planning is very important. When extreme weather conditions cause delays over the entire arriving fleet, holding stacks are installed at the three Initial Approach Fixes (IAFs) around Schiphol. In the current operational environment, little support is offered to the holding stack controller (ACC) to gain an overview of the effects of speed and wind on the turn times and difference between inbound and outbound leg velocity. With increased support, the controller will be able to make decisions based on representative information and with that, deliver inbound aircraft to Approach (APP). The (expected) resulting increased EAT adherence should lead to more orderly traffic in the TMA, improving capacity and workload.


Janjaap Wijnker (BSc)Evaluating the accuracy of information provided by the (D-1) OPS plan

In early 2020 LVNL implemented the OPS plan with the objective to improve the alignment of traffic demand with available capacity. This can be achieved by improving the predictability of the operations and make this transparent and accessible for the stake-holders. Every day the PRE-TACT unit develops an OPS plan for the following operational day. The plan contains two types of information, external factors that might impact the capacity, and recommendations for the most optimal operations. The recommendations are based on the external factors, for example the predicted traffic demand and weather forecast. These two factors contribute to the configuration of runways, and the runway selection determines the required capacity. In order to for LVNL to improve possible deficiencies of the OPS plan, the aim of this research study is to evaluate the accuracy and precision of the predicted traffic demand. The analysis focusses on the difference between predicted and actual traffic demand on a 20 minute resolution. In addition, the implications of factors contributing to the proposed runway configuration will be assessed since the use of different runways could have a significant impact on the capacity.


Mathijs Post (MSc)Air Traffic Flow Management for Amsterdam Airport Schiphol

Air Traffic Flow Management is a measure to optimize the flow of traffic in the European air transportation system. Flights are planned such that these can be operated with as little delay as possible. However, on the day of operation many changes can still happen. Amsterdam Airport Schiphol is the biggest contributor to Airport ATFM Delay in Europe, meaning many flights are delayed because of congestion or other airport related reasons at Schiphol. Besides Airport ATFM Delay, the arrival punctuality of flights at Schiphol can be improved. More insights into the causes and interactions of operational parameters is necessary to understand the main contributors for Airport ATFM Delay and arrival delay. A Bayesian Network is proposed, which is a Probabilistic Graph Model that can find interactions between variables and can identify the operational conditions leading to Airport ATFM Delay and arrival delay.


Christophe Vakaet (MSc) – 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.


Bart Bouwels (MSc) – Air Traffic Management Concept for Off-Idle Continuous Descent Operations at Schiphol

Due to the continued growth of the aviation industry, emission and noise production are at an all-time high. In order to reduce this, conventional approaches could be replaced by continuous descent approaches (CDA). These eliminate all level segments, greatly reducing the average thrust setting, resulting in large reductions in noise and emission production. The problem with almost all CDA procedures is that it makes it much more difficult to predict the future position of an aircraft since it flies its own optimal descent profile, with zero thrust. This results in a need for more separation, greatly reducing the airport capacity. This can largely be solved by using a fixed, constant descent angle for all aircraft. Assessing the robustness of such a concept for a high capacity airport is therefore an important stepping stone towards actual implementation.