The introduction of Trajectory Based Operations (TBO) is set to change the operation on all levels of Air Traffic Control (ATC), including aerodrome control. Here, adherence to a planned four-dimensional trajectory is important to achieve a stable operation. At the same time, this concept provides possibilities for support tools to be used in ATC, by making use of new data and information. This research presents the Take-off Timing Support Tool (TTST) for aerodrome control, and more specifically runway control, at Amsterdam Airport Schiphol. It is incorporated into the already existing Electronic Flight Strip System and features a time axis on which flight strips can be placed. By dragging departures along the time axis a planning and sequence can be constructed, while taking into account the provided solution space to prevent conflicts. An experiment conducted with the TTST showed that professional air traffic controllers used the information from the tool in their decision-making, leading to a decrease in conflict count, and it was demonstrated that a stable planning could be established. Therefore, the TTST is a suitable platform to support TBO in aerodrome control and assists air traffic controllers with time-based control. No significant difference in departure interval was present. The workload did increase moderately.

This research investigates the role of time prediction accuracy in optimizing Continuous Descent Operations (CDO) within the aviation sector, with a specific focus on assessing the additional benefits brought forth by the integration of Air-Ground Datalink technologies. Continuous Descent Operations, characterized by uninterrupted and efficient descent profiles, hold promise for reducing fuel consumption, emissions, noise, and overall operational costs. However, the extent to which accurate time predictions contribute to the success of CDO remains a critical yet understudied aspect.

This paper explores the impact of Automatic Dependent Surveillance - Contract (ADS-C) on air traffic control (ATC) procedures, focusing on operational efficiency and safety margins in lower airspace. Through 64 simulation configurations, the study evaluates how varying airspace density, separation buffer size, and vertical error in ADS-C data influence operational metrics, such as fuel burn, track miles, and flight time. The simulations utilize synthetic ADS-C data with a 100% equipage rate, providing insights into how ADS-C can be applied to manage intersecting flight trajectories. Results indicate that separation buffer size is the most influential factor. Smaller buffers lead to significant reductions in fuel burn, track miles, and flight time compared to the baseline, though this comes at the expense of increased conflict risks. Airspace density demonstrated trends where higher densities showed the greatest fuel savings but more conflicts, highlighting a trade-off between operational efficiency and safety. These findings support the role of ADS-C in increasing predictability and improving trajectory management, both of which are key to Trajectory-Based Operations (TBO). By improving the accuracy of aircraft intent and trajectory data, ADS-C can optimize flight paths and enable more efficient air traffic management. However, carefully considering separation buffers and airspace density is essential to balance efficiency with safety.

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.

As aviation recovers to pre-pandemic levels large amounts of Air Traffic Flow Management delay also return, as the traffic at airports and in airspaces reaches their old levels. These delays have a yearly cost of around 500 million euros in the European Civil Aviation Conference area and are detrimental to the experience of passengers. This paper proposes a change in the interaction between the A-CDM process at Schiphol and EUROCONTROL's Network Manager, varying at what point the slot improvement process for regulated flights is stopped; providing more transparency in the network with this change. The resulting change in ATFM delay is investigated by modelling these two systems and freezing the slots at a set time, using historical input data to accurately model the turnaround process. The results generated using the described methods are inconclusive. More data and an additional implementation of using the CTOTs calculated by the model in the simulated turnaround are needed in order to make statistically sound conclusions on whether changing the T-DPI-s horizon has any effect. Nevertheless, this paper still presents insights and a novel framework for continued research into the subject.

The airspace in western Europe is one of the most complex airspaces globally. With the air space already operating near maximum capacity, innovations are needed to increase airspace efficiency. This research aims to design and test a debunching concept for inbound air traffic to increase the efficiency of the arrival traffic stream. A probabilistic debunching concept is created for the Initial Approach Fix using Probability Density Functions fitted on the errors in predicted arrival times provided by the EUROCONTROL Enhanced Tactical Flow Management System Flight Data messages (EFD). A bunching probability is detected when two or more aircraft have a probability of arriving at the Initial Approach fix simultaneously or within the required Wake Category Separation. A debuncher is created using a Constrained Genetic Algorithm that decreases the bunching probability by imposing en-route delay on arriving air traffic. The results show that the bunching probability increases with shorter prediction horizons as the uncertainty in the arrival estimates decreases. It is shown that with the probabilistic debunching method, it is possible to decrease the delay in the Arrival Manager by imposing delay en-route. However, at prediction ranges before 40 minutes before arrival at the IAF, the decrease in the AMAN delay is not consistent, indicating that the trajectory prediction uncertainty at this range is too high. Furthermore, the decrease in the AMAN delay is often lower than the imposed delay by the debuncher, showing that the decrease in AMAN delay comes at the cost of extra delay en-route. It is concluded that when the uncertainty in the trajectory predictions is decreased, the effectiveness of the debuncher increases and the effect on the Arrival Manager is improved, indicating improved arrival efficiency.

Taxi time predictions are used by air traffic controllers to optimally release aircraft from the gate such that efficiency losses due to queuing are minimized, while runway capacity is maintained. More accurate taxi times can therefore result in improved airport surface operations and reduce air traffic controller workload. This article proposes a methodology to develop taxi time predictor and applies this methodology to Schiphol airport. The methodology combines novel data-driven predictors with different improvements and extensive performance evaluation. One such improvement involves using recent taxi time prediction errors to improve upcoming taxi time predictions. During evaluation, this article extends conventional analysis by analyzing different prediction horizons and performance metrics. Applying the methodology at Schiphol airport resulted in a predictor that increased the fraction of flights with a taxi time error of less than two minutes from 64.41% to 67.91% compared to the currently operational manual decision tree predictor.

As a result of the current evolution in the ATM system, a fundamental shift in the ATC work domain is foreseen from ad-hoc tactical to more strategic, 4D (i.e., space and time) trajectory management. Both the SESAR programme in Europe
and the NextGen programme in the US envision a central role for the human operator, to be aided by high-level automated decision support tools. In an attempt to prototype such support tools, a 4D trajectory management interface was previously designed and experimentally validated. To improve on the maturity of this concept, effects of wind and trajectory uncertainty were integrated into the interface in this present work. Using six professional controllers, the redesigned interface was evaluated in a realistic 4D inbound traffic peak scenario within the Dutch airspace, where small control spaces require a mixed tactical-strategic form of ATC. Results indicated that operators were able to successfully combine conflict and arrival time management in a highly complex traffic scenario despite the added display complexity, although further research will be needed to confirm these findings in a statistically relevant context.

On final approach, an Approach (APP) Air Traffic Controller (ATCo) is responsible for keeping sufficient separation between aircraft lining up on the ILS. The current industry standard is to separate these aircraft with a minimum distance, called Distance-Based Separation or DBS. European regulation requires all European airports to implement separation based on time (Time-Based Separation or TBS) before 2024. Due to this implementation, effectively changing the APP ATC task from a geometrical to a time-based problem, and because of further complications such as the European re-categorisation of aircraft types, experts fear that the theoretical gains attainable by using TBS will not be fully realised. In this research, a display tool concept to aid APP ATCos in realising the full potential of TBS, the Ideal Turn-In Point (ITIP) display is designed and evaluated with respect to the current state of the art. The ITIP display assists controllers in selecting optimal approach strategies starting from the moment aircraft enter the Terminal Control Area. The display aims to assist the operator by showing the possibilities and restrictions in the system rather than giving (restricting) advisories. In an initial proof-of-concept experiment, comparing the ITIP display to the current industry state of the art display, promising results were found; the ITIP display was shown to maintain safety and increase efficiency, whilst maintaining controller workload. The current industry state of the art display is a tool designed by the National Air Traffic Services, currently operational at London Heathrow Airport.