Conflict Probability Based Strategic Conflict Resolution for UAS Traffic Management

In this paper, we present a strategic conflict resolution method based on the conflict probability estimation, in the context of Unmanned Aircraft System (UAS) Traffic Management. We first elaborate a classic approach for flight trajectory generation in a designated realistic airspace environment, which is then smoothed by B-spline algorithm to achieve higher realism. The trajectories are extended to 4-dimensional Operational Volumes (OV) following the current UTM development visions. This forms the basis for performing a coarse conflict screening process, as the initial part for conflict detection, primarily based on identifying any OVs overlapping in temporal and spatial. Next, we look into the captured OVs and apply a well-studied conflict probability estimation approach, which contributes to a refined and more accurate conflict detection outcome. To resolve the potential conflicts, we propose two models including First-Come, First-Served (FCFS) and optimisation, both embedded with the probability-based conflict detection. In the FCFS approach, flights are delayed in the order of their submission, while the optimisation model aims at cherry-picking flights to seek the optimal solution. Numerical experiments with various case studies are performed to assess the effects with and without such probability concern, as well as different implementation strategies in real world. Results suggest that, allowing OVs’ overlapping to some extent does not necessarily incur conflict over an acceptable probability, whereas the efficiency of airspace use could be improved.