Autofly-aıd: havada çarpışmadan kaçınma için esnek ve uyarlamalı 4 boyutlu dinamik rota yönetimi ile uçuş karar destek sistemi

This thesis, namely, AUTOFLY-Aid Project, aims to develop and demonstrate novel flight deck automation support algorithms and tools for potential conflict avoidance and performance-optimal flight using "dynamic 4D trajectory management". The developed automation support system is envisioned not only to improve the primary shortcomings of existing on-board traffic collision avoidance systems (e.g. TCAS), but also to develop new conceptual add-on avionics and procedures enabling intent data exchange, decision support systems with augmented reality and flight control hand-over implementation in dynamically evolving scenarios. The main concepts which has been developed in AUTOFLY-Aid project are a) design and development of the mathematical models of the full composite airspace picture from the flight deck perspective, as seen/measured/informed by the aircraft flying in the sky of the SESAR and NextGen 2020+ vision and beyond, b) design and development of a dynamic 4D trajectory planning algorithm can generate at real-time flyable (i.e. dynamically and performance-wise feasible) alternative trajectories for both short-term and mid-term scale across the evolving stochastic composite airspace picture and c) development and testing of the automation support system on a Boeing 737-800 Flight Simulator with conceptual procedures, automated flight control implementations, and reality augmented based decision support demonstrations providing the flight crew with quantified and visual understanding of evolving situation. Evaluation from a purely centralized tactical intervention model towards a more strategic planning and progressive introduction of more autonomous and decentralized tactical operation with more proactive systems are key concepts in both NextGen and SESAR future ATM paradigm shift vision. Implementing of these new-generation ATM concepts will significantly change the human role in the ATM system by considering "best decision place", "best decision time" and "the best decision player". Through these objectives, AUTOFLY-Aid envisions to take some of the work off the controller by delegating some responsibility to flight decks in an efficient manner. The developed automation system offers persistent in-flight hazard and flight efficiency monitoring and tactical flight trajectory planning as a function of look-ahead time and dynamically changing environmental/operational conditions (and with uncertainty reduction in a feedback loop) obtained via both in-flight sense and ground-air data link. The automation system switches autonomy level according to the required response time in order to find "the best decision player" through asking "where are men better at, where are machines better at". In mid-term safety assurance mode, it is expected that pilot uses a visual decision support tools (e.g. tunnel-in-the-sky visualization) with fully situational awareness for safe and performance optimal flight. These visual advisories are generated by fusing all tactical level information feed from both on-board sensing and ground-air data/information exchange. If the reaction time permits, the system allows pilots to freely switch between the generated alternative plans, modify the solution or request re-planning. In any case of the immediate potential threat is detected (i.e. immediate response is required or late response is detected), the autonomous system may take over the flight control to solve safety-critical situation happening "almost surely" (e.g. midair collision, terrain collision etc.). This hybrid approach allows dynamic role assignment by switching between defined autonomy level modes in terms of the "required response time".