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

published_or_final_version / Computer Science / Doctoral / Doctor of Philosophy

From 2010 to 2030, the number of instrument flight rules aircraft operations handled by Federal Aviation Administration en route traffic centers is predicted to increase from approximately 39 million flights to 64 million flights. The projected growth in air transportation demand is likely to result in traffic levels that exceed the abilities of the unaided air traffic controller in managing, separating, and providing services to aircraft. Consequently, the Federal Aviation Administration, and other air navigation service providers around the world, are making several efforts to improve the capacity and throughput of existing airspaces. Ultimately, the stated goal of the Federal Aviation Administration is to triple the available capacity of the National Airspace System by 2025. In an effort to satisfy air traffic demand through the increase of airspace capacity, air navigation service providers are considering the inclusion of advisory conflict-detection and resolution systems. In a human-in-the-loop framework, advisory conflict-detection and resolution decision-support tools identify potential conflicts and propose resolution commands for the air traffic controller to verify and issue to aircraft. A number of researchers and air navigation service providers hypothesize that the inclusion of combined conflict-detection and resolution tools into air traffic control systems will reduce or transform controller workload and enable the required increases in airspace capacity. In an effort to understand the potential workload implications of introducing advisory conflict-detection and resolution tools, this thesis provides a detailed study of the conflict event process and the implementation of conflict-detection and resolution algorithms. Specifically, the research presented here examines a metric of controller taskload: how many resolution commands an air traffic controller issues under the guidance of a conflict-detection and resolution decision-support tool. The goal of the research is to understand how the formulation, capabilities, and implementation of conflict-detection and resolution tools affect the controller taskload (system demands) associated with the conflict-resolution process, and implicitly the controller workload (physical and psychological demands). Furthermore this thesis seeks to establish best practices for the design of future conflict-detection and resolution systems. To generalize conclusions on the conflict-resolution taskload and best design practices of conflict-detection and resolution systems, this thesis focuses on abstracting and parameterizing the behaviors and capabilities of the advisory tools. Ideally, this abstraction of advisory decision-support tools serves as an alternative to exhaustively designing tools, implementing them in high-fidelity simulations, and analyzing their conflict-resolution taskload. Such an approach of simulating specific conflict-detection and resolution systems limits the type of conclusions that can be drawn concerning the design of more generic algorithms. In the process of understanding conflict-detection and resolution systems, evidence in the thesis reveals that the most effective approach to reducing conflict-resolution taskload is to improve conflict-detection systems. Furthermore, studies in the this thesis indicate that there is significant flexibility in the design of conflict-resolution algorithms.