Key decisions in the air traffic control system are supported by various technical systems. The most important include conflict detection and resolution (CD&R) systems. The main subject of this paper is a medium-term conflict detection system (MTCD). An excessive number of false alarms is one of the major functional problems of these systems in current implementations. They make the whole idea of CD&R systems less effective. The aim of this study is to present the concept of the system for the initial assessment of the overall level of complexity of the traffic situation. It should become the first stage of the MTCD system algorithm. The paper presents a general scheme of the model to assess the traffic situation based on fuzzy sets theory, and more specifically on the theory of fuzzy inference systems. Choosing this type of the model is justified by the lack of precise and well-defined relationships between the factors influencing the traffic situation complexity and its assessment, which is largely subjective. The paper discusses the input and output linguistic variables and briefly presents the results of simulation experiments conducted with the use of fuzzy inference system implemented in the SciLab environment. Experiments have confirmed the effectiveness of this solution and indicated the possibility of its inclusion in the MTCD system algorithm as a first stage. This will improve the MTCD software behavior with respect to alerting a controller about a detection of the conflict and supporting him/her by the development of proposals for its solution.
Rytter, A., & Skorupski, J. (2017). The Concept of Initial Air Traffic Situation Assessment as a Stage of Medium-Term Conflict Detection. In Procedia Engineering (Vol. 187, pp. 420–424). Elsevier Ltd. https://doi.org/10.1016/j.proeng.2017.04.395