Dynamic Unmanned Aircraft System Traffic Volume Reservation Based on Multi-Scale A* Algorithm
Jun Xiang, Victor Amaya, Jun Chen · AIAA SCITECH 2022 Forum · 2022
View Video Presentation: https://doi.org/10.2514/6.2022-2236.vid With the recent advancements in unmanned aircraft system (UAS) technology, unmanned aerial vehicles (UAVs) are widely used or proposed to carry out various daily tasks in the low altitude airspace, such as delivery and urban air mobility. In order to safely integrate the UAS traffic into the congested airspace in the urban area, the current UAS traffic management system proposed by NASA will reserve a static traffic volume for the whole planned trajectory, which is safe but not efficient. In this paper, we propose a dynamic traffic volume reservation method for the UAS traffic management system based on a multi-scale A* algorithm. The planning airspace is represented as a multi-resolution grid, where the resolution will get coarser as the distance to the planning drone gets larger. Therefore, each drone will only need to reserve a temporary traffic volume along the finest flight path in its local area, which helps release the airspace back to others on the far side. Moreover, the multi-scale A* can run nearly in real-time due to a much smaller search space, which enables dynamically rolling planning to consider updated information. The presented numerical results support the advantages of the proposed approach.