Alumni

Lydia Hoogendijk (BSc)

Automation in service provision: Reducing ATCO workload while achieving sustainability goals

Becoming an Air Traffic Control Officer (ATCO) is a rigorous and demanding process, requiring candidates to pass a series of aptitude, psychological, and physical assessments. The low success rate in training results in a shortage of ATCOs, leading to increased workload for those already in service. This, combined with rising air traffic volumes and the urgent need for sustainable aviation operations, underlines the necessity of enhanced automation in air traffic management. Furthermore, the transition from the AAA system to the iCAS system in the coming years is a key priority for LVNL. This research, grounded in the SESAR Master Plan 2025, explores automation opportunities within the iCAS system in comparison to the AAA system. The aim is to identify how automation can help address the challenges faced by ATCO’s, reduce their workload, and support more sustainable aviation operations, ultimately contributing to the efficiency and safety of air traffic management.

Graduated: July 2025

Lydia Hoogendijk (BSc)

Rosemarijn Remmers (BSc)

Evaluating Safety Measures for Converging Runway Operations at Schiphol Airport

At many airports around the world, runways are used in different ways, including parallel, diverging, and converging operations. Each type of operation comes with its own challenges, depending on the airport’s layout and the way aircraft arrive and depart at the same time. At Schiphol Airport, due to its runway layout, not only parallel and diverging runways are used, but also converging runways. These converging runway operations require special safety measures to ensure that all aircraft can land and take off safely. These measures follow both international and Dutch safety regulations. However, maintaining a high level of safety is an ongoing process. It is important to regularly review whether these measures are effective and how they work in practice. In 2022, after thorough research, LVNL introduced new safety measures to improve the operation of runway combinations where aircraft take off and land on converging runways. These new measures are specifically designed for use in good visibility conditions and during the uniform daylight period. To ensure continuous improvement in safety, it is essential to assess how these measures are applied in daily practice and whether they effectively reduce operational risks. By analyzing real-world data and operational procedures, this research will provide insights into their effectiveness and identify any potential areas for further improvement.

Graduated: July 2025

Rosemarijn Remmers (BSc)

Matthijs Slobbe (MSc)

ETA predictions based on accurate weather

The weather is something that impacts everyone on a daily basis and much research has been done to improve weather forecasting in the past. This is also the case in the aviation industry, using traditional data sources as well as aircraft measurements. Previous research in this domain has developed the Meteo-Particle (MP) model which constructs a wind field based on data collected by aircraft and UAVs. Research has also been done with new physically inspired machine-learning approaches to create wind fields. This research, with the ultimate goal being to reduce uncertainty in aircraft estimated time of arrival (ETA), intends to approach the problem of creating accurate 3D wind fields with a diffusion neural network, filling in the gaps where there is no aircraft data available. Previous models struggle with non-uniform wind fields, this new approach presents an opportunity for better reconstruction of the wind fields under these conditions.

Graduated: July 2025

Matthijs Slobbe (MSc)

Suze Garstman (BSc)

Implementing FF-ICE release 1

The concept of FF-ICE is to reduce the limitations of the current flight plan 2012 in order to support the future environment as detailed in the global ATM operational concept. Which concept is to support future ATM operations. Through the EU implementing rule 118/2021 phase 1, a.o. the introduction and use of a new flight plan will be mandatory 2025, December 31st. To reach this goal it is necessary to investigate if and how these new flight plan alterations can and will be supported by LVNL and her stakeholders.  Today’s flight plan presents the ATCO and other stakeholders the initial intend of a flight. No modifications during the flight are possible. However, FF-ICE phase 1 is designed to manage this problem specially towards Trajectory Based Operations. This new flight plan will be introduced to provide richer route/trajectory descriptions to support the efficient use of air space worldwide. This research aims to identify the alterations already in place or needed within LVNL and her stakeholders to comply with EU implementing rule 118/2012.

Graduated: May 2025

Suze Garstman (BSc)

Sander Poelstra (MSc)

Optimizing taxiway maintenance planning using ground control workload limits

Currently, the taxiway maintenance planning at Amsterdam Airport Schiphol (AAS) is determined based on technical necessity, and often not based on the impact on ground operations. Including the impact on operations is then done at a later stage, resulting in maintenance projects being pushed through because it is not operationally feasible. An important operational effect that depends on maintenance planning is the impact on the workload of ground controllers. This workload should not become too high due to taxiway maintenance, otherwise safety and ground capacity at the airport will deteriorate. It is therefore essential to study the relationship between the closure of taxiways due to maintenance and the workload of ground controllers in order to test the feasibility of maintenance plans. In this thesis project, this relationship is studied and it is clarified when and for how long taxiways can be closed for maintenance at AAS such that the workload of ground controllers remains within acceptable limits.

Graduated: February 2025

Sander Poelstra (MSc)

Vincent van Dijk (BSc)

Enhancing predictability and efficiency in the aircraft towing process through improved real-time information sharing

In complex and dynamic environments, real-time data sharing is more important than ever. It’s no surprise that Eurocontrol’s Airport Collaborative Decision Making (ACDM) system, which focuses on improving the efficiency and resilience of airport operations by optimizing resource use and enhancing air traffic predictability through real-time data sharing, is yielding positive results. For both inbound and outbound flights, this system has minimized delays caused by miscommunication or a lack of transparency among stakeholders. However, when it comes to towing operations, which share many operational similarities with flight movements, the same improvements haven’t been realized. In towing operations, it’s still common for there to be poor information exchange between stakeholders, making the process unpredictable and inefficient. This research aims to improve the predictability and efficiency of aircraft towing through enhanced real-time information sharing, potentially reducing disruptions, congestion, and APU runtime, while optimizing tow truck use and overall operational performance.

Graduated: February 2025

Vincent van Dijk (BSc)

Tex Ruskamp (MSc)

Reducing uncertainty for Flow Management of arriving traffic at Schiphol before departure

At LVNL a Decision Support System (DST) is used to support ACC Supervisors and Flow Managers (FMP) in their decisions to issue flow regulations to the Network Manager of Eurocontrol in Brussels. The horizon at which flow regulations are typically issued is three to four hours before arrival at Amsterdam Schiphol Airport. However, at this time horizon, a significant portion of the arriving traffic is still on the ground at the so-called out-stations. Previous research has shown that a significant portion of the uncertainty in the predicted traffic demand is originated in the pre-departure phase. This research aims to develop a machine learning model that makes an improved estimation of the Take Off Time.

Graduated: January 2025

Tex Ruskamp (MSc)

Vera Buis (MSc)

Improving fog forecasts for Amsterdam Airport Schiphol using machine learning algorithms

LVNL uses a Decision Support Tool (DST) to manage and mitigate delays up to four hours ahead. Accurate weather forecasts play a crucial role in accurately predicting the airport’s capacity. Specifically low visibility conditions due to fog severely limit the capacity due to the large separation between aircraft that is needed to ensure safe operations. Fog can arise and dissipate within a matter of minutes. Besides that, it can occur on very small spatial scales, as small as a couple hundred metres. Ordinary weather forecasting tools are often incapable of capturing this very small-scale and short-lived nature of fog. Using machine learning algorithms to forecast fog poses a promising solution to this issue. Using observations on the airfield, visibility forecasts can be made for multiple areas at the airport. A small-scale, accurate fog forecast greatly increases the capability of air traffic controllers to anticipate lower capacities, and therefore timely mitigate delays.

Graduated: November 2024

Vera Buis (MSc)

Thijs Scheffers (MSc)

Effects of increased trajectory predictability by ATS Datalink on air traffic management operations in lower airspace

The latest generation of Air-to-Ground Datalink (AGDL), known as Air Traffic Services B2 (ATS B2) is now being introduced into European airspace. As mandated by the European Union (EU), effective from 31 December 2027, aircraft receiving their first airworthiness certification on or after this date must be capable of downlinking and processing ADS-C Extended Projected Profile (EPP) data, as part of ATS B2. An important element of this AGDL implementation is the availability of detailed trajectory information with flight intent. This application leads to improved predictability, as it allows for more accurate predictions of an aircraft’s intentions and destination. Increased predictability enables improvements in key areas, such as safety, flight efficiency, and environmental impact. The aim of this research is to determine the impact of this improved predictability on the design of air traffic control procedures in lower airspace around Schiphol Airport.

Graduated: November 2024

Thijs Scheffers (MSc)

Alexandru Măgdălinoiu (MSc)

Supporting executive inbound flight sequencing: improving Expected Approach Time adherence

An important bottleneck in managing inbound traffic capacity is the limited size of the Terminal Manoeuvring Area, which should not become crowded by aircraft arriving from the Control Area. This is done by arrival metering, a process entailing sending aircraft through the Initial Approach Fix (IAF) at pre-established Expected Approach Times (EAT). Currently, area controllers are required to deliver aircraft at the IAF at their EAT ± 120 seconds. Reducing this window in the near future would allow for less buffer times between aircraft to increase capacity, potentially allowing implementation of time-based separation at the IAF as an initial step towards trajectory based operations. This research aims to produce a visual decision support tool to aid the aircraft sequencing process and achieving EAT adherence at the IAF, that is compatible with the currently in use or upcoming systems used in the Amsterdam Area Control Center. To avoid significant changes to the modus operandi of controllers, the aim is to show the user the operational constraints and focus on expediting traffic. An experiment was conducted with eight professional controllers to compare the newly developed tool with a rendition of the current interface. The results are positive, indicating less deviation from the EATs in all participants and overall lower participant workload as a result of using the proposed decision support tool.

Graduated: October 2024

Alexandru Măgdălinoiu (MSc)