Air Traffic Simulation Framework for Testing Automated Air Traffic Control Solutions

As air traffic control (ATC) automation advances, simulation environments become essential for testing and validating novel solutions before deployment. This study presents a modular framework that integrates real air traffic data to simulate controlled and uncontrolled airspace environments for automation assessment. The framework consists of a two-layer structure: a traffic simulation layer for generating and updating aircraft positions, and an upper layer for managing control agents and traffic commands. It uses ADS-B data to simulate realistic conditions, incorporates randomized traffic generation, and enables pilot–controller interactions. The system supports various operational modes, from simple data recording to fully interactive control scenarios. Interfaces allow external algorithm integration for traffic prediction, conflict resolution, and controller workload evaluation. A case study demonstrates the framework’s ability to assess a basic control algorithm’s performance under increasing traffic density. This open-source, MATLAB-based simulation environment supports robust, repeatable ATC automation testing using real-time or recorded traffic data. Its flexible architecture and clearly defined interfaces enable customization for diverse research applications, including sectorization studies, flow management, and workload estimation.