A Survey on Artificial Intelligence (AI) and eXplainable AI in Air Traffic Management: Current Trends and Development with Future Research Trajectory

Air Traffic Management (ATM) will be more complex in the coming decades due to growth and increased complexity of aviation has improved order maintain safety. It is agreed that without significant improvement this domain, safety objectives defined by international organisations cannot achieved a risk incidents/accidents envisaged. Nowadays, computer science plays major role data management decisions made ATM. Nonetheless, despite this, Artificial Intelligence (AI), which one most researched topics science, not quite reached end users ATM domain. In paper, we analyse state art with regards usefulness AI within aviation/ATM includes research work last decade ATM, extraction relevant trends features, representative dimensions. We analysed how general eXplainable (XAI) works, analysing where why XAI needed, it currently provided, limitations, then synthesise findings into conceptual framework, named DPP (Descriptive, Predictive, Prescriptive) model, provide an example its application scenario 2030. concludes systems need further for their acceptance end-users. The development appropriate methods including validation authorities end-users are key issues needs addressed.