Air traffic controller agent model for free flight

The objective of this research was to design and demonstrate an agent-based modeling and analysis tool for evaluating air traffic controller (ATC) performance under free flight air traffic management (ATM), and to develop distributed decision-making model to investigate the potential for collaborative problem-solving under free flight. We developed a set of intelligent agent models representing ATC and pilot behavior in free flight. These models contain simplified representations of information processing and situation assessment applied to air traffic conflict detection. They also contain detailed air traffic conflict resolution models applying collaborative decisionmaking via inter-agent negotiation. We demonstrated the operation of a limited-scope prototype in a set of simulation trials designed to exercise the multi-agent decision-making model under a spectrum of free flight air traffic configurations. The results showed that our agent models are capable of performing on-line learning to support global situation awareness (SA) in the air traffic environment. The nature of conflict resolution maneuvers negotiated by the agents varied with conflict geometry in a manner consistent with intuitive expectation.