Currently, there is a significant increase in oceanic air traffic. The Federal Aviation Administration (FAA) is attempting to keep pace with this traffic. Automation is being planned in the airline and Air Traffic Control (ATC) system; eventually, all oceanic functions will be part of the FAA Advanced Automation System (AAS). The Oceanic Display and Planning System (ODAPS) capabilities include oceanic flight data processing, conflict probe, flight strip printing; and aircraft situation display capabilities. The Fight Data Input/Output (FDIO) device is currently being used as the main controller input device to the ODAPS. The objective of the Oceanic Air Traffic Control System (OATCS) is to replace the FDIO device with a system that will provide more flexibility and assistance to the oceanic air traffic controller in interfacing with the ODAPS The OA TCS being proposed by this research and thesis is an interim system in support of planned automation. The OATCS will provide the controller with the ability to scroll, and search through previous received ODAPS update, alert, and response messages, and to compose and edit ODAPS flight plan messages. The OATCs will augment and enhance the current functionality of the FDIO system of the ODAPS by providing high technology workstations similar to AAS. The OATCS also will provide the capability to process Automatic Depending Surveillance (ADS) position reports by replacing ODAPS peripherals to improve the working environment for oceanic controllers, the ARINC Communication Center, and the pilot. In addition, the OATCS will support a future two way data link between the oceanic controller and the pilot. / Master of Science

Air traffic control teams are responsible for the safe and efficient control of air traffic through corresponding air sectors. When long term imbalances develop between a team's control capability and the level of control demanded by the sector traffic, inefficiencies develop in the control process. These inefficiencies are seen in sectors where traffic is delayed or rerouted due to overworked control teams, while other sectors have low levels of traffic and underutilized control teams. One technique for resolving these imbalances is to change the area of responsibility for the control team by changing the boundaries of their air sector. However, the determination of the appropriate sector boundary change for improving the situation is a qualitative question for Air Route Traffic Control Center officials. This effort reviews the existing expressions for determining the level of controller workload and presents a decision support model for quantitatively evaluating alternative sector boundary changes. A user specified workload expression is separated into workload components and describes the level of controller workload for each sector in a sectored airspace. The model requires a graphical description of the initial sector arrangement, the values for the controller workload components and a description of the proposed boundary change. The changed sector arrangement is computed from this information and the model provides a description of the resulting air sectors and their associated values for the workload components. The result of the proposed boundary change is seen in the changed sector arrangement and the amount of change is determined by comparing the values of the workload components of the initial and changed sector arrangements. Each sector arrangement is described with a data file and numerical tables. The data file is used for plotting a two-dimensional representation of the sectored airspace. The tables quantify the values of the workload components for each air route in a sector at the sector, air route, and air route section levels. In this manner, the model provides a more objective approach for officials to balance sector workloads. / M.S.

A crescente demanda por transporte aéreo tem provocado um aumento na densidade do fluxo de aeronaves no espaço aéreo. A sobrecarga cada vez maior de aeronaves nos setores estáticos do espaço aéreo, cujos controles são de responsabilidade dos controladores de tráfego aéreo, provoca um estado de alerta constante no gerenciamento do tráfego aéreo. Uma única falha na monitoração e controle dos setores, realizadas pelos controladores de tráfego aéreo, pode por em risco a vida de centenas de pessoas. Para garantir a segurança do espaço aéreo, o controlador de tráfego aéreo tem que realizar várias tarefas no seu dia-a-dia, estando exposto a uma carga de trabalho. Uma das frentes de pesquisas que busca balancear a carga de trabalho dos controladores de tráfego aéreo é a Re-setorização Dinâmica. O objetivo deste trabalho de pesquisa é investigar como se comporta a carga de trabalho dos controladores de tráfego aéreo com a utilização da Re-setorização Dinâmica, tendo como estudo de caso um espaço aéreo brasileiro de alta densidade de aeronaves. / The growing demand for air transportation has caused an increase in the density of aircraft flow in the airspace. The overload of aircraft in airspace sectors, which are under the air traffic controllers\' responsibility, causes a permanent alert state in the air traffic management. A single controller\'s fault with monitoring and controlling a sector may endanger hundreds of people\'s lives. The air traffic controller has to perform many activities daily in order to assure safety to the air space, being exposed to a certain workload. The Dynamic Resectorization is a research line in this direction that aims to balance the workload of the air traffic controllers. The goal of this research work is to investigate the behavior of the air traffic controller workload through the use of Dynamic Resectorization, having as a case study a Brazilian air space with high aircraft density.

A crescente demanda por transporte aéreo tem provocado um aumento na densidade do fluxo de aeronaves no espaço aéreo. A sobrecarga cada vez maior de aeronaves nos setores estáticos do espaço aéreo, cujos controles são de responsabilidade dos controladores de tráfego aéreo, provoca um estado de alerta constante no gerenciamento do tráfego aéreo. Uma única falha na monitoração e controle dos setores, realizadas pelos controladores de tráfego aéreo, pode por em risco a vida de centenas de pessoas. Para garantir a segurança do espaço aéreo, o controlador de tráfego aéreo tem que realizar várias tarefas no seu dia-a-dia, estando exposto a uma carga de trabalho. Uma das frentes de pesquisas que busca balancear a carga de trabalho dos controladores de tráfego aéreo é a Re-setorização Dinâmica. O objetivo deste trabalho de pesquisa é investigar como se comporta a carga de trabalho dos controladores de tráfego aéreo com a utilização da Re-setorização Dinâmica, tendo como estudo de caso um espaço aéreo brasileiro de alta densidade de aeronaves. / The growing demand for air transportation has caused an increase in the density of aircraft flow in the airspace. The overload of aircraft in airspace sectors, which are under the air traffic controllers\' responsibility, causes a permanent alert state in the air traffic management. A single controller\'s fault with monitoring and controlling a sector may endanger hundreds of people\'s lives. The air traffic controller has to perform many activities daily in order to assure safety to the air space, being exposed to a certain workload. The Dynamic Resectorization is a research line in this direction that aims to balance the workload of the air traffic controllers. The goal of this research work is to investigate the behavior of the air traffic controller workload through the use of Dynamic Resectorization, having as a case study a Brazilian air space with high aircraft density.

published_or_final_version / Computer Science / Doctoral / Doctor of Philosophy

Thesis (MComm (Industrial Psychology))--University of Stellenbosch, 2009. / The aim of this study was to determine whether there is a relationship between Emotional Intelligence, Stress and Coping Strategies in the occupation of air traffic control. The focus was to determine whether the Emotional Intelligence of an Air Traffic Controller might have an effect on the recognition and management of stressful situations, and influence the way they select coping strategies. Due to a lack of research on air traffic control in South Africa, focus are not only on the stress levels of Air Traffic Controllers, but also how their Emotional Intelligence could assist in the recognition and management of the stress they experience, and ultimately then contribute to select appropriate Coping Strategies. A literature study discussed the role of Air Traffic Controllers, and factors that contribute to them experiencing stress. The constructs of Stress, Emotional Intelligence and Coping were elaborated on in detail. The constructs were defined as follows: Stress, as any demand eliciting a negative emotional state, that exceeds an individual’s resources to cope; Emotional Intelligence, as the process of emotional information processing consisting of the dimensions of Self Awareness, Self Regulation, Motivation, Empathy and Social Skills (Rahim & Minors, 2003); and Coping as the efforts to manage environmental and internal demands and conflicts which tax or exceed a person’s resources (Lazarus & Launier, 1978).

The study focuses on the Human Factors (HF) discipline and its role in improving aviation safety and efficiency within Air Traffic Control (ATC). The objective is to contribute to a better understanding of the ATC work domain and identify opportunities for improving performance, safety and efficiency. The research also aims to understand air traffic controllers' (ATCs) experience of the Mil i-ATC alarm system and propose enhancements to improve performance. Data collection was executed through observational research at a military air traffic control tower, and semi-structured interviews with ATCs, moreover, Work Domain Analysis and Thematic Analysis were employed for data analysis. The findings highlight key factors influencing ATC operational efficiency and safety, including communication, air traffic management, and alarm management, that is realized through social, technical and physical means. Moreover, workload, stress, situational awareness, teamwork, and decision-making were identified as interrelated elements within ATC. To enhance the Mil i-ATC alarm system, the study recommends considering alarm presentation, taking into account context and operational impact. Moreover, alarms without operational significance and false alarms are identified to cause frustration and undermine the reliability of the alarm system. Further research is necessary to determine the feasibility of presenting action plans directly in the system and how alarms should be listed. It is recommended that future studies focus on sustaining ATCs' motivation and alertness during monotonous tasks or low workload situations. Additionally, it is important to determine the appropriate level of automation in ATC management systems and evaluate controllers' trust in these systems.

The aviation industry is under increasing pressure to reduce cost and manage the increased number of passengers. One area under pressure is the Air Traffic Control. The Air Traffic Control will in a foreseeable future manage the introduction of drones also known as Unmanned Aerial Vehicles by integrating them into civil airspace with manned aircraft. Drones are lacking consensus from authorities with regards to standards due to their rapid expansion. Given their size, shape and speed, they can also pose threats to manned aircrafts and there is a need to address them in an Air Traffic Management system interoperating with manned aircrafts. The purpose in this study is to identify what considerations to make when automating complex system elements with respect to safety. Safety involves all the different stakeholders in the air transportation system, which is a Safety critical System. Furthermore, the aim is also to identify areas in which European Operational Concept Validation Methodology (E-OCVM) can be complemented with. Standard E-OCVM is missing specific assessment criteria with regards to safety and how it can interact with other standards. The approach is thereby to use various standards with focus on Systems Engineering to complement E-OCVM since it is lacking with regards to how it is used to validate Air Traffic Control systems. To capture the complexity of automating elements of an industry involving many stakeholders, a qualitative analysis was conducted in this project, using a System Engineering approach with four standards A-SLP, A-RLP, A-DAS and A-SAS. A-SLP and A-RLP are two general standards while A-DAS and A-SAS are focusing on the contexts of aircrafts and software development. Empirical data was gathered by semi-structured interviews of seven experts within the relevant areas in the field. From the review of the four standards, it was found that they can for instance complement E-OCVM in how software errors can lead to a failure condition among other ways. The main identified considerations faced with an integration of drones into civil airspace, is to manage the human interaction with the introduced Air Traffic Management systems. More specifically, the human element must be involved from the training phase in the development of systems in a Safety Critical System to minimize risk. Furthermore, redundancies that are built into the system has to, not only be able to put the system into a safe state, but also be carefully analyzed in how they interact with other systems to avoid misjudgement for the Air Traffic Controllers. Lastly, to obtain specific details on how interoperability could occur using standards, the standards used in this study refer to usage of other documents and standards. Standards specifically tailored for the operational context of drones would facilitate further testing and implementation of their integration into civil airspace. Given that different standards were used to complement the EOCVM standard, a set of unified standards are required that are proportional with the type of drones, the type of operations and in the environment that they are operating in. This will be needed to fulfill the European vision of safe integration of drones and needs thereby to be carried out in a global manner, thus also share experience with other actors to advance the new technology adaptation.

No description available.

Air traffic controllers (ATCos) monitor flight operations and resolve predicted aircraft conflicts to ensure safe flights, making them one of the essential human operators in air traffic control systems. Researchers have been studying ATCos with human subjective approaches to understand their tasks and air traffic managing processes. As a result, models were developed to predict ATCo actions. However, there is a gap between our knowledge and the real-world. The developed models have never been validated against the real-world, which creates uncertainties in our understanding of how ATCos detect and resolve predicted aircraft conflicts. Moreover, we do not know how information from air traffic control systems affects their actions. This Ph.D. dissertation work introduces methods to evaluate existing ATCo action prediction models. It develops a prediction model based on flight contextual information (information describing flight operations) to explain the relationship between ATCo actions and information. Unlike conventional approaches, this work takes data-driven approaches that collect large-scale flight tracking data. From the collected real-world data, ATCo actions and corresponding predicted aircraft conflicts were identified by developed algorithms. Comparison methods were developed to measure both qualitative and quantitative differences between solutions from the existing prediction models and ATCo actions on the same aircraft conflicts. The collected data is further utilized to develop an ATCo action prediction model. A hierarchical structure found from analyzing the collected ATCo actions was applied to build a structure for the model. The flight contextual information generated from the collected data was used to predict the actions. Results from this work found that the collected ATCo actions do not show any preferences on the methods to resolve aircraft conflicts. Results found that the evaluated existing prediction model does not reflect the real-world. Also, a large portion of the real conflicts was to be solved by the model both physically and operationally. Lastly, the developed prediction model showed a clear relationship between ATCo actions and applied flight contextual information. These results suggest the following takeaways. First, human actions can be identified from closed-loop data. It could be an alternative approach to collect human subjective data. Second, the importance of evaluating models before implications. Third, potentials to utilize the flight contextual information to conduct high-end prediction models.