TITLE: The role of Artificial Intelligence in Air Traffic Management
AUTHORS: Denis Odić, Damir Džubur, Muharem Šabić
ABSTRACT: Artificial intelligence (AI) is increasingly being used in air traffic management to improve efficiency, safety, and overall performance in the aviation industry. AI algorithms can analyze vast amounts of data in real-time, such as weather patterns, airspace capacity, and aircraft trajectories, to predict delays and optimize flight schedules accordingly. AI and Machine Learning (ML) are already contributing to a wide spectrum of value opportunities in the aviation/ATM industry, from non-safety critical to safety critical applications. Another transversal component is AI-enabled simulation platforms, where augmented reality offers the possibility of creating a testing and validation environment where new and innovation aviation concepts like U-space can be explored. This paper will show an example of possible use of AI for Dynamic Airspace Sectorisation (DAS). The idea for a possible DAS solution that is going to be a part of this paper is divided in three parts. First one is fuzzy clustering used for clustering of air traffic as initial allocation of flights, the second are Voronoi diagrams that will provide a design of an initial airspace structure in sectors and the third one is an evolutionary algorithm which goal is to optimize the sectorisation. The goal of this approach is to evaluate airspace organization/sectorisation under both operational and economical aspects.
KEYWORDS: Artificial intelligence (AI), Air Traffic Management (ATM), Dynamic Airspace Sectorisation (DAS), Machine learning (ML)
PAGES: 96-102
DOI: