A decentralized event-based predictive navigation scheme for Air-Traffic Control

This paper presents an approach for the multiagent navigation and conflict resolution problem, that considers the issue of performance. We present a decentralized predictive navigation scheme that combines the Decentralized Navigation Functions methodology with the Model Predictive Control (MPC) framework while preserving the former´s collision avoidance and convergence guarantees. Aircrafts, flying at constant altitude, are modeled as unicycles. Performance criteria are encoded in a cost functional. Due to decentralization, each agent does not take into account the decisions of others in the control law calculation, resulting in performance discrepancies. Therefore, we employ event-triggered executions in our scheme. The improved performance is demonstrated through simulations.