This study explores the application of cognitive work analysis (CWA) and ecological interface design (EID) in the development of a novel display system for a Dash 8 Q300 aircraft retrofitted with a hydrogen-electric fuel system. By leveraging CWA and EID, this research aimed to address the challenges of managing cognitive complexity in next-generation aviation systems, focusing on designing interfaces that enhance pilot decision-making and situational awareness. These analytical frameworks informed the design process, ensuring that the displays were tailored to the cognitive demands of the pilots. To validate the effectiveness of the proposed designs, interviews were conducted with a regional commercial pilot, an airworthiness engineer, and a test pilot. These interviews provided qualitative insights that confirmed the applicability of the CWA/EID-based designs, particularly emphasizing the need for simplicity and clarity in time-constrained regional operations. The study highlights the importance of focusing display content on critical and abnormal conditions to reduce cognitive load, aligning with rule-based behavior (RBB) frequently employed by pilots. Future work should involve controlled human-in-the-loop experiments with a larger participant pool to empirically test the proposed display designs.

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.

Enroute Air Traffic Controllers (ATCOs) determine the appropriate course of action by scanning radar displays to identify and select a flight that requires clearances to ensure safe and efficient operations within their airspace sector. After selecting a flight of interest, ATCOs visually compare the flight parameter displayed in the flight labels to assess the impact of potential flight control actions on the sector safety. Expected surge in global air traffic will make it difficult for ATCOs to compare flight parameters, leading to delayed responses and increased workload. This research proposes a flight filtering mechanism based on interacting flight trajectories with spatio-temporal proximities to guide ATCOs’ attention toward potential interaction flights after selecting a flight of interest. ATCOs will find potential interaction flights more saliently as non-interacting flights fade once the flight of interest is selected. This approach targets ATCO’s pre-attentive phase of visual processing, alleviating additional perceptual and cognitive efforts in finding and processing information during conflict detection and previewing clearances. Experiment results with eight subject matter experts as participants showed no significant differences in the safety, operator performance, and perceived workload while controlling traffic due to demanding task requirements and strategy variation among participants. Nonetheless, participants expressed positive feedback regarding the assistance offered by filtering in fading non-interacting flights. No significant differences in objective measures coupled with filtering’s positive perceptions indicate filtering did not negatively affect the performance, suggesting further research with optimal balance between task requirements and participant expertise to evaluate the flight filtering concept.

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.

The joint management of airspace by human controllers and automated agents is gaining prevalence in nextgeneration Air Traffic Control (ATC). In such settings, human controllers are challenged with maintaining situation awareness while dealing with intricate and often opaque automated technologies. This study probed the potential of a concept interface, which augments traditional radar displays, to facilitate human controller-automation teamwork. With visual explanations and interactive elements, it intended to make the control behavior of automated agents transparent and comprehensible to human operators. The primary objective was to explore whether features from a non-conventional design could offer insights for designing interfaces for highly automated ATC operations. The concept was tested in a prototype-based user experience evaluation with static traffic scenarios, involving 15 active air traffic controllers from the Maastricht Upper Area Control Center. Results indicated that the visual explanations of the interface enabled controllers to comprehend the plans and reasoning underlying automation’s behavior. A significant correlation between controllers’ evaluations and their attitudes toward novel technologies underlines the influence of pre-existing beliefs about automation on the acceptance of new interface tools. Future research is warranted to streamline parts of the design and further investigate the interface’s capacity for explaining automation’s actions in dynamic, real-time scenarios.

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.

In the future, Air Traffic Controllers are expected to work together with more advanced computer-based automation that can automatically take action. The main challenge is then how to design computer-based tools such that they foster acceptance among air traffic controllers. One possible approach to foster acceptance is by matching the automated decisions and actions to individual human problem-solving styles, the so-called strategic conformance. Another approach is by making the automated tool more transparent and thus interpretable. Previous research aimed to combine these two approaches by making use of the Solution Space Diagram, a decision-support tool for Conflict Detection and Resolution, as a visual feature for a supervised machine learning method that aimed to generate individual human prediction models. Results were promising, but prediction accuracy could be significantly improved. In this study, the impact of feature engineering and a revised machine learning architecture on prediction accuracy will be investigated. This is done by evaluating different feature engineering and architecture options using data generated by a simulation in which Conflict Detection and Resolution is performed. It was found that a Convolutional Neural Network can accurately predict exact resolutions using regression and a more optimized architecture is introduced which significantly increases predictive performance. Furthermore, it is concluded that a larger solution space results in a slight increase in predictive performance whereas the use of a color scheme with more colors does not necessarily result in a higher predictive performance.

Future ATM systems will rely on automation to make operations more efficient. Creating insight into the inner-workings of automation, also known as agent transparency, is expected to play an important role for effective human-machine collaboration. This research proposes an ecological approach to increase agent transparency in automated rerouting for en-route traffic. For the purpose of this study, an ecological interface for the rerouting task, developed in a previous study, was visually augmented with the constraints guiding the behavior of an experimental path-planning algorithm. This was done in two different ways: a top-down and bottom-up approach. The top-down approach starts at the goal of the system and subsequently adds information related to the physical implications, while the bottom-up approach has the reversed order. The design was tested in a human-in-the-loop experiment with ten participants. Results show that higher levels of transparency significantly increased actual and perceived understanding of the agent’s decisions. Furthermore, the top-down approach performed significantly better in questions related to the strategy of automation, while the bottom-up approach was found more useful for making predictions about the agent’s rationale for making certain decisions. Future research should investigate how agent and domain transparency could be combined and should test situation awareness in addition to understanding of automation. Additionally, because only static situations were investigated in this study, the effects of a dynamic work domain featuring various time-critical situations should be analyzed in future research.

The Continuous Descent Approach (CDA) offers reduced noise emissions and fuel consumption, but its main complication is the lack of predictability regarding the Estimated Time of Arrival (ETA). A suggested solution is to develop a pilot support interface for the execution of a fixed flight path angle CDA for a selected ETA, with thrust not being bounded to idle. Initially, the trajectory calculation method of CDA and the boundary cases were defined. Then, a two-fold interface was designed for planning and execution, based on Ecological Interface Design (EID), with a Vertical Situation Display (VSD) playing a central role, and it was tested by five pilots over different wind conditions. The pilots' on-time performance was satisfactory, while they worked with the cues and suggested enhancements to accommodate their strategy. The validation of this approach can lead to applying the CDA in real flight conditions, without limiting itself to low traffic times.

The current ATC system is seen as the most significant limitation to coping with an increased air traffic density. Transitioning towards an ATC system with a high degree of automation is essential to cope with future traffic demand of the airspace. In recent studies, reinforcement learning has shown promising results automating Conflict Detection and Resolution (CD&R) in Air Traffic Control. The acceptance of automation by Air Traffic Controllers (ATCos) remains a critical limiting factor to its implementation. This work explores how automation can be developed using Deep Q-Learning from Demonstrations (DQfD), which aims to be transparent and conforms with strategies applied by ATCos to increase acceptance of automation. Reward decomposition (RDX) is used to monitor the learning and to understand what the agent has learned. This study focuses on two-aircraft conflicts, in which the state of the controlled and observed aircraft is represented by raw pixel data of the Solution Space Diagram. It was concluded that pre-training on demonstrations speeds up learning and can increase strategic conformance between the solutions provided by the RL agent and the demonstrator. Next to increasing conformance, results also show that DQfD can improve its policy with respect to the suboptimal demonstrations used during training. Finally, RDX has allowed the designer to examine the policy learned by the RL agent in more detail.

The expected increase in unmanned aerial vehicle (UAV) traffic in European airspace raises concerns regarding the human factors of tower controllers. Dynamic geofences offer tower control a means to safely separate UAVs from manned traffic, without direct interactions with individual UAVs. A preliminary support interface was designed, supporting the operator in separating UAV traffic from manned traffic, while minimising impact on (high priority) UAV efficiency. The effects of traffic conditions and geofence size on control behaviour, safety, efficiency and interface usage were investigated in a human-in-the-loop experiment with active tower and air traffic controllers. Results show that geofences are considered a useful tool in maintaining safety, that larger geofences significantly increase average traffic separation and that the effect on efficiency differs per traffic scenario. Performance could be improved by increasing transparency and predictability of UAV routing, for example by optimising the geofence structure around the runway and by more clearly presenting high-level UAV information to the controller. Further work is needed to investigate controller behaviour and performance in an environment with control over both UAV and manned traffic, considering the temporal aspect of geofences, as well as a broader range of UAV missions and capabilities.

This study has researched what are defining factors on the attitude toward a new technology within the group of Area Control (ACC) at Luchtverkeersleiding Nederland (LVNL) and how these factors shape an Air Traffic Controller’s (ATCo) attitude toward the technology in an exploratory way. The outcomes of the research suggest that dominant factors are result demonstrability, output quality, job relevance, subjective norm and (timeliness of) involvement in the development process. First, the work domain of air traffic control and the functioning of holding patterns were researched and a description of these things was given, based on interviews with air traffic controllers and on literature. It was found that the largest challenge when holding at LVNL is adherence to Expected Approach Time (EAT), and that this is caused by two things: the first is a lack of accurate and integrated information on the impact of a control decision on EAT adherence, the second is that current practice of ATCos is to aim for a 2:00 minute deviation from the EAT, which is the current error margin they are allowed to operate on. It was found, based on interviews with two professional area controllers and one other expert from LVNL, that in current practice an ATCo makes estimations of when to give a turn-to-IAF command based on a rule of thumb with a holding loop timing of four minutes and by extrapolating the history dots of the aircraft. However, analysis of historical holding pattern data shows that lap times often take six or seven minutes and that wind severely influences the in- and outbound ground speeds, making both the four-minute loop time and history dot extrapolation unreliable estimators. A support tool was designed that gives a prediction of the time it takes to reach the IAF from different locations, taking into account aircraft characteristics and wind. The new tool was designed such that it is in accordance with the layout and style of present LVNL systems. It involves two things. First, a prediction of the EAT adherence error upon giving an immediate turn-to-IAF command in the form of a delta-T in the aircraft label. Second, and a prediction of the turn-to-IAF locations at which an EAT adherence error of +120s, +110s, ..., 0s, 10s, ...-120s will be achieved, in the form of colored dots (ECOL dots) on the vertical view and the top view radar screen. The social situation at LVNL was described based on interviews with two professional area controllers and one other expert from LVNL. Indications were found for two opposite things. On the one hand, that (some) ATCos are willing to innovate and actually take initiative in innovation processes, and on the other hand, that (some) ATCos have a strong resistance toward technological system innovation. Regarding collaboration between groups, itwas found that the relation between ACC and Approach Control (APP) that is characterized by skepticism on the skills of the other party. Finally, it was found that ATCos take pride in the way they execute their job and are willing to work hard to achieve the goals they believe match their job description. In doing this, ATCos have indicated to value their autonomy and the idea that the effort they put in actually adds value for the full Air Traffic Control (ATC) process. Besides interviews to describe the situation at LVNL, case studies were done to research innovation in other organizations that showed similarities to the context of LVNL. Three things were found. First, ensuring people can contribute and influence the innovation from early stages of the innovation process is a promising factor that seems to influence a person’s attitude toward using the innovation in a positive way. Second, the lack of implementation of innovations has caused skepticism under ATCos. Third, the TAM is a suitable framework to further explore how area controllers at LVNL’s attitude toward innovations manifests itself. To be able to use the TAM in the framework, first, literature on the TAM has been reviewed. It has been found that there are different versions of the TAM that include or exclude several variables. For the present research, the most suitable version of the TAM was determined to be the TAM2, using the following external variables: result demonstrability, output quality, job relevance, image, subjective norm, experience, voluntariness, age. Next to the TAM in the framework, literature was reviewed on several factors surrounding the interaction with support systems, where autonomy and trust were found to be of a valuable contribution to the framework in the present research. The operationalization of the framework was done using survey questions, a semi-structured interview, and results from letting ATCos interact with the system innovation concept (the tool). It was found that some factors of the TAM could be questioned straightforward in either the survey or the interview, while for other factors it was necessary do design multiple questions and depend on the type of answers given by the participants. Since the research is exploratory, it was decided to keep the interview setup semi-structured to ensure participants would be able to outline defining factors for their attitude toward innovation relatively freely, instead of needing to keep them within a predefined set of factors. From the performed case study, where 10 ATCos participated in an experiment in which they had to manage two holding scenarios, with and without the tool, the following things were learned. First, three of the external variables defined in the framework played the largest role for participants’ perceived usefulness of the tool were result demonstrability, output quality and job relevance. Second, it was found that subjective norm impacts the attitude towards use for the participant group. A mismatch was found between the participants’ attitude toward innovation in general and the way the participants thought their colleagues viewed system innovations. Subjective norm was also found to be of influence on the participants personal objective in the level of EAT adherence they aim to obtain in their day-to-day work. Third, participants linked the external variables not only toward perceived ease of use and perceived usefulness, as is the case in the TAM, but also to attitude towards use. Finally, it was found that participants appreciated being part of an innovation process rather than being presented with the final solution, which was further improved by the fact that the concept was visibly not perfected yet (even though it was functioning, it was clear it was still under development and showed some minor issues in e.g., the stability of the computer program).

Aviation has experienced a huge leap in technology since the Wright Brothers first took flight in 1903. From the first propeller powered wood and canvas aircraft to the modern day aluminium and carbon fibre reinforced plastics jet aircraft [33], aviation has evolved. Next to the evolution of materials and aircraft going from propeller to high bypass ratio turbofan engines, the flight deck of aircraft has seen an incredible advance in technology. It has gone from countless gauges displaying all kinds of information to the pilots towards a digital flight deck, displaying information on screens. The latest step has been the introduction of touchscreens, allowing pilots to interact with the displayed information directly [2]. The novel use of touchbased interfaces allows for a lot of benefits like the direct interaction with information as mentioned, however, there are several drawbacks when using a touchbased interface. A main one is the difficulty of interaction with a touchbased interface when in a turbulent motion environment [6]. Research has been done before on the usability of touchbased interfaces when in an atmospheric turbulence environment, such as by Cockburn et al. in 2017 [6], but this work focuses on mitigating the effects of the atmospheric turbulence. On the other hand, research has been done on constructing a predictive model for the usability of a touchscreen, as performed by Bi et al. in [3], but this was in a stationary environment. In this research thesis a predictive model will be constructed that incorporates the effects of atmospheric turbulence into Fitts’ Law, [11], and Finger Fitts’ Law specifically, [3], in order to predict the usability of touchbased interfaces under various levels of atmospheric turbulence.

Augmented reality displays are a promising means to improve the safety of helicopter hovering in brownout conditions. However, previous research has often combined conformal with non-conformal elements in such displays, potentially leading to visual clutter. In this paper, two purely conformal displays are proposed, and their effectiveness is compared with a baseline condition in good visibility depicting the ADS-33 hover course. The first display contains a grid ground texture and a box indicating the hover target position; the second bears close resemblance to the ADS-33 course. Two pilots participated in a simulator experiment in which the effects of display configuration and vehicle dynamics on hover performance, control activity, pilot workload and situation awareness were examined. Results show that performance similar to that in good visibility can be achieved with the grid display, although workload and situation awareness deteriorated. Performance with the second display was worse, likely due to lack of available optic flow. Linear vehicle dynamics led to lower workload than a non-linear model, but not to better performance. For future research, it is recommended to improve availability of longitudinal positioning cues in the grid display, and to investigate the usefulness of that display also in good visibility.

The use of automated conflict detection and resolution tools for air traffic control seems inevitable. Air traffic controllers will then take the role of automation supervisors, a role which is generally unsuitable for humans. Gamification, the use of game elements in non-gaming contexts, shows promising results in mitigating the effects of boredom. This project presents and experimentally tests a proposed implementation of gamification within an air traffic control work environment. Fictional aircraft are superimposed among automatically controlled real traffic, thus creating fictional conflicts that need resolving. System supervisors are given the task of supervising the behaviour of a fully automated conflict detection and resolution system while routing fictional aircraft safely and efficiently through the sector, avoiding conflicts with other aircraft (both real and fictional). Experiment results show that the presence of fictional aircraft increased reported concentration levels among participants, as well as improved supervisory control performance.

Before an aircraft enters the Terminal Manoeuvring Area (TMA) a delay may need to be introduced due to capacity limits. An Air Traffic Controller (ATCo) has the opportunity to introduce a holding procedure. When multiple aircraft need to be delayed in this form a holding stack may be formed. This holding stack is formed above the Initial Approach Fix (IAF). Current industry standard is able to achieve an accuracy within two minutes of planned Estimated Approach Time (EAT), at which the aircraft is planned to fly over the IAF and proceed to the TMA. In this research a display tool to aid Area Controllers (ACC) in realising a more accurate delivery and improving their situational awareness is designed, called the Stack Planner (SP). The SP assists controllers with choosing an optimal holding leg time for aircraft in the holding stack to adjust their IAF flyover time. The display aims to assist ATCo by showing the possible space of their control actions as well as system constraints. In an initial proof-of-concept experiment, comparing the SP display with a baseline state of the art display, promising results are found; the SP display shows a more manageable workload with increased situational awareness that scales with scenario complexity. The new display also shows the potential to move from minute accuracy to second accuracy. Future studies would need to investigate the extent to which scenario complexity plays a role in accuracy of delivery for both baseline and SP displays.

Driving with driver assistance systems utilising haptic shared control (HSC) can lead to annoyance, or even disuse, when the intent of both entities differs. In order to increase compliance and acceptance of these systems, this study explores two types of visual information projected onto the outside scenery. One visualisation portrays only the intended trajectory of the HSC system, whereas the other visualisation complements this by showing the manoeuvring boundaries of the car. These visualisations were evaluated in a human-in-the-loop simulator study focused on supporting an early and late car overtake manoeuvre, initiated by HSC. Although most participants reported a preference for visualisation of both the intended trajectory as manoeuvring boundaries, results in terms of torque conflicts and position conflicts indicated no significant differences between the visualisations. Subsequent analysis, however, indicated that this was probably caused by the variability in how participants used the visualisations in combination with their apparent preferences in performing the overtake manoeuvre. In conclusion, supporting HSC with visual information does not improve compliance, but shows an improvement in acceptance. For future work it is recommended to further investigate the impact of visualisations on intra-driver variability.

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.

In an effort to further evaluate the effects of Ecological Interface Design on acquiring expertise, this paper presents the results of an investigation into how Ecological Interface Design could possibly promote discovery learning processes in the Air Traffic Control domain through the application of an instructional design model, and how it could thereby support novices in picking up an implicit rule of thumb. A between participants experiment (N = 28) was performed through which participants, divided over two groups, were guided by means of a training script developed according to the Four-Component Instructional Design model. Participants from both groups had to perform a simplified Conflict Detection & Resolution task in which the rule of thumb was implicitly integrated. In addition, one group received additional support from an ecologically designed cognitive tool that was unexpectedly removed after a transfer manipulation. Results show that applying an instructional design method to the experiment design indeed leads to a more structured learning process and participants making significantly more use of optimal strategies, corresponding to the execution of the rule of thumb. Additionally, being trained with the cognitive tool leads to an increased awareness of the implicit rule of thumb but does not lead to an increased use of this rule. It was furthermore found that participants, who were trained with the tool, showed increased dependency on this tool. It is therefore recommended to further extend the experiment design and investigate whether including additional instructional design elements, such as phased visual elimination of the elements of the cognitive tool, could reduce participants’ dependency.