Trajectory Coordination based on Distributed Constraint Optimization Techniques in Unmanned Air Traffic Management

In this paper, we explore a multiagent-based deconfliction strategy in Unmanned Air Traffic Management (UTM). We equip autonomous unmanned aerial vehicles (UAV) with decision capabilities to update their trajectories (4D contracts) when facing unpredictable events or when priority trajectories are added to the airspace. Current initiatives for UTM envision a multi-layered management system where the lowest one is composed of either autonomous UAV or human-operated one, that may have to react to incidents and emergencies, while sticking to the contracted 4D trajectories. We propose an agent-based approach, where UAVs, being aware of close potential conflicts provided by the UTM communication layer, can coordinate directly, without central UTM control, to update trajectories and solve resulting conflicts in a decentralized manner. This reduces the access to a central decision bottleneck and permits reactive deconfliction. We propose both uncoordinated and DCOP-based coordinated behaviors, that we experimentally evaluate on dense scenarios within a limited area with numerous 4D contracts, potential incidents and emergency procedures.