Path Planning of Large Fixed-Wing Unmanned Aircraft Subject to Specific Operational Ground Risk Assessment

Driven by the booming applications of low-altitude airspace, large fixed-wing unmanned aircraft systems (UAS) are increasingly used in logistics, yet quantifying their ground risk and planning a safe path remain less addressed. Inspired by the specific operations risk assessment (SORA) framework, we develop a path planning method subject to quantitative ground-risk model for fixed-wing UAS. The critical area of impact is first estimated based on characteristic dimension and flight velocity. Thereafter, the intrinsic ground risk class (R) of aircraft is evaluated considering the population density. A critical risk level is applied to the resultant intrinsic ground risk class matrix, which generates a map with pseudo non-fly-zones. Thereafter, the A* algorithm is used to plan a feasible path that bypasses the high-risk areas. The proposed method is applied to an unmanned airplane operating in a scenario. The case study implies that the proposed method offers a quantitative basis for trajectory optimization of large UAS operating in intercity and intracity scenarios.