Multi-Agent systems for air traffic conflicts resolution by using a causal analysis of spatio-Temporal interdependencies

Current Air Traffic Management research programs (i.e. Single European Sky ATM Research (SESAR), next generation air transportation system (NextGen)), try to overcome airside capacity shortages while improving cost- efficient operations and safety. An increment in the airspace traffic density can lead to congested traffic scenarios for which it becomes necessary to develop new safety- procedures to tackle air traffic complexity. This paper presents an innovative conflict resolution system that mitigates present airside latent capacity by a cooperative resolution mechanism in which a negotiation between aircraft-Agents deals with conflict free resolution trajectories. A causal analysis using Colored Petri Net (CPN) formalism is presented as a key approach to analyze the state space of a congested traffic scenario to avoid emergent dynamics and downstream negative effects on the surrounding traffic.