A Network-Based Conflict Resolution Approach for Unmanned Aerial Vehicle Operations in Dense Nonsegregated Airspace

To accommodate the growing demand for airspace access by various entrants, the worldwide air traffic-management system is undergoing the process of airspace integration, where unmanned aerial vehicles are at the forefront of change. As heterogeneous aircraft operate in nonsegregated airspace with distinct performances and separation requirements, numerous interactions and conflicts are expected, as is the conflict resolution (CR) difficulty that follows. Considering the domino effect, where one maneuver decision made on an individual may generate a cascading influence on its neighbors, an optimal resolution order that adjusts the fewest aircraft possible is crucial to resolution efficiency. Therefore, an in-depth investigation into couplings among aircraft is essential, which is not widely seen in the literature. To fill this gap, we propose a network-based CR approach to adjust a minimal number of conflict-critical aircraft while guaranteeing a global conflict-free environment. Specifically, a conflict network is first developed to analyze the pairwise conflict relations among aircraft, where the detection of a certain aircraft is termed as an edge, and conflict severity is measured as the weight of this edge. Moreover, an improved PageRank algorithm is designed to identify key aircraft that are bottlenecks of system safety. A centralized CR sequence allocation (SA) is further implemented to ensure that these key aircraft assume major resolution responsibility and deconflict first. Simulation results show that the approach maintains high resolution efficiency in terms of fewer aircraft adjustments and computing time as well as traffic efficiency in terms of reduced velocity and path deviations under mixed-operation scenarios.