Design of Intelligent Decision Support Model for ATC System by Integrating Multi-Source Data

Facing the demand for intelligent transformation of air traffic management, this paper constructs an intelligent decision support system for air traffic control based on deep reinforcement learning. By designing route conflict detection algorithms, traffic flow situation assessment methods and emergency decision-making recommendation algorithms, intelligent decision-making support with multi-source data fusion is realised. The research results are of great significance in improving the efficiency of airspace utilisation and the level of control decision-making intelligence, and provide a new idea for promoting the intelligent upgrade of the air traffic control system.