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Nowadays, the development of technologies that improve airspace operation in many aspects is essential since the importance of air transportation for society is increasing. The airspace, although, may become more complex considering the integration of these aircraft due to the issues regarding the social acceptance of autonomous systems (e.g., familiarity between Air Traffic Controller - ATCo - and Unmanned Aircraft System - UAS) and the uncertainty in terms of operation (e.g., hardware failures, software failures, interfaces failures, and misunderstanding of instructions). However, standard procedures (e.g., landing procedures) may not be followed in complex situations due to safety constraints (e.g., loss of minimum aircraft separation). As a result, ATCos play an essential role in maintaining appropriate levels of safety and efficiency by conducting aircraft using Vectoring Points (VPs). Hence, ATCos must be trained to deal with such challenging scenarios, especially in resource-constrained regions, e.g., in the final sector of the Terminal Control Area (TMA), where the aircraft are guided to the landing phase. The primary goal of this research is to propose a framework for training Air Traffic Controllers (ATCos) to deal with complex situations (e.g., considering many aircraft as well as severe weather conditions) in the final sector considering the UAS integration into the National Airspace System (NAS). This approach is divided into a set of modules for (1) proposing the training scenarios, (2) proposing solutions, and (3) evaluating the quality and feasibility of the solutions proposed. The aspects evaluated in the solutions provided for the proposed scenarios are ATCo workload and efficiency.
Neto et al. (2024) studied this question.