Estimating the impacts of the wind field size, wind speed, turbulence, and no-fly zones on unmanned aerial vehicle flights in urban areas

Safety assurance for unmanned aerial vehicle (UAV) flights has become increasingly crucial for advancing urban low-altitude transportation networks. The complex wind environment generated by dense building layout and narrow streets poses significant challenges to low-altitude UAV flights. For efficient and economical transportation, UAVs must navigate these conditions by avoiding dangerous wind zones while minimizing flight distances. This study established an integrated framework combining Reynolds-averaged Navier–Stokes-based computational fluid dynamics simulations with multi-objective path planning algorithms for planning short and safe UAV flight paths in complex urban wind fields. We evaluate critical factors influencing urban wind fields, including study area dimensions, wind directions, flight altitudes, and grid resolutions of wind data extraction. Results reveal that wind direction impact depends critically on UAV exposure to the approaching wind (headwind, tailwind, or crosswind). Generally, flight paths at high altitudes (∼90 m) exhibit greater deviation from the original path compared to low altitudes (∼30 m) due to increased exposure to regions of strong wind and high turbulence intensity. Furthermore, flight paths optimized using wind data extracted at finer grid resolutions (4 m) are shorter than coarser resolutions (12 m). Flight path planning employs an A* algorithm optimized for three objectives: minimizing path length, avoiding hazardous wind speeds, and circumverting areas of high turbulence intensity. This framework was used to evaluate the impact of urban wind environments on flight paths. The findings offer crucial insight for designing reliable and sustainable systems required for future urban air mobility management.