At airports, taxiway maintenance is a complex task affecting airport ground operations, specifically airport surface movement operations managed by ground controllers. It is expected that taxiway maintenance also affects the task load experienced by ground controllers. However, to our best knowledge, no studies were performed so far to quantify and assess this influence. To fill this gap, this research studies the impact of taxiway maintenance on the task load of ground controllers. It is essential to develop this understanding to ensure that taxiway maintenance is planned safely, efficiently, and robustly. This research uses Schiphol Airport as a use case, for which an existing airport surface movement simulator was used to model the ground traffic with a single-agent trajectory planning algorithm. To realistically represent the traffic patterns at Amsterdam Schiphol Airport, the simulated model was calibrated using real trajectory data and expert opinion.
To quantify the task load of ground controllers, the well-known Dynamic Density model and a novel measure, based on controller's mental re-plannings, were used and compared to each other. Based on a maintenance scenario, simulations were performed for two runway configurations, with the aim to study the differences in task load between the nominal and maintenance scenario for different flight schedules. The main outcome of this analysis is that conflicting flows, resulting from taxiway maintenance, have a significant contribution to the task load of ground controllers. It was further found that the effects of these conflicts on the task load are localized and do not propagate further to other areas, and other ground controllers who do not have responsibility over the specific area in question do not experience this impact in task load.

The Dutch Air Traffic Control has implemented fixed approach trajectories within approach control during night operations when traffic density is low. During the day, when traffic density is higher, vector-based operations are used. The Dutch Air Traffic Control aims to implement fixed approach trajectories when traffic density is high. This shift from the current vector-based operations will allow aircraft to perform a continuous descent and fly around inhabited areas, reducing the emissions and noise. To improve the capacity of the landing runway in strong headwind conditions, time-based separation is envisioned. Separating aircraft on time will result in a constant runway capacity in all wind conditions. However, to make these changes possible, additional decision support tools are required to assist controllers and reduce their workload. This paper discusses the use of a new toolset, centered around a time-space diagram which shows the expected arrival time and distance-to-go to a selected reference waypoint. Results of an experiment with eight professional air traffic controllers show that the added tools allowed future conflicts to be solved sooner and with fewer instructions. Aircraft followed the fixed approach trajectories better in the latter stages of the approach when compared to current vector-based operations. Although a slight increase in runway capacity was observed with the new toolset, it was not statistically significant. The workload of the controllers did not show a difference when using the new toolset. In conclusion, the added tools enabled the controllers to combine fixed approach trajectories with time-based separation. However, to reduce perceived workload, future designs should aim to integrate the time-space diagram on the main radar screen such that controllers do not need to switch attention between screens.

Air traffic sector demand and capacity balancing is an important process to enable safe and efficient flight execution. In current operations, demand and capacity are determined based on schedules and flight plans. In reality, disruptions to flights create a different situation that may not have been anticipated by the Air Navigation Service Provider (ANSP). Wrong demand forecasts may cause unnecessary network regulations or inefficient flight execution. This research aims to improve air traffic sector demand forecasting, by exploring machine learning based trajectory prediction. In light of the Trajectory Based Operations (TBO) concept that is being developed within Air Traffic Management (ATM) research, a trajectory-based approach is taken to improve demand forecasts. To achieve this, the transformer neural network was identified as a suitable generative model that can predict aircraft trajectories. Using available traffic messages from the Eurocontrol Business-to-Business (B2B) connection, and actual trajectories obtained from the OpenSky ADS-B repository, a successful transformer neural network was built. This trajectory predictor could accurately generate trajectories, outperforming the flight plan and other neural network approaches by a large margin. For demand prediction, the introduction of improved trajectories provided small gains that could potentially lead to more stable predictions.

The Compound Annual Growth Rate (CAGR) of the aviation industry is predicted to be 4.1% from 2015 to 2045 [23].In recent years, however, increasing public pressure has been put on the industry to further reduce noise and carbonemissions. This can be done by eliminating all horizontal flight segments during the approach phase, reducing theaverage thrust. Such an approach is called a Continuous Descent Approach (CDA) and has been the subject of manystudies. Ideal CDAs are flown with idle thrust, which results in the largest fuel flow reduction but which has a verybig drawback; The vertical profiles of ideal CDAs vary greatly between aircraft making it difficult for ground-basedsystems to predict the exact position of an aircraft ahead of time ([35]). In order to deal with this added uncertainty,additional separation is needed. This greatly reduces the capacity, which means that such a concept can only beused when there is little traffic. ([26]) This greatly limits the benefits since there is very gain during such times. Thereare other types of CDAs, which take away the need for this added uncertainty, however. These are called a fixed orconstant Flight Path Angle (FPA) approaches. Where the FPA during ideal CDAs is optimised by each aircraft’s FlightManagement System (FMS) for that particular flight, an average is used for this type. This average is then flown witha small, off-idle, amount of thrust. Which means that although in general the noise and emission reductions aredecreased when compared to ideal CDAs, ([35], [8]) the capacity is increased ([25]).In this thesis, fixed-route fixed FPA approach procedureswill be designed for the SchipholTMA and compared to currentdesigns. This will be done by trading off the environmental benefits for capacity under robustness and flexibilityconstraints. Although only part of the descent occurs inside of the TMA, most of the emission and noise reductionscan be achieved here as the inefficient level segments that usually occur here are moved to the upper airspace ([32]).