Identification of no-fly zones for delivery drone path planning in various urban wind environments

Abstract

A drone delivery system, characterized by its low energy consumption, high efficiency, and extensive coverage capability, has been adopted as an effective solution to overcome the limitations of traditional ground transportation. However, due to strong interactions between urban structures and wind, the wind environment in the low-altitude airspace of urban areas poses significant safety risks for drone operations, a challenge that remains unresolved. To mitigate these risks, this study presents a methodology for precisely defining the no-fly zones (NFZs) for drone operations using computational fluid dynamics (CFD) simulations. Three hazardous indices—safe, deviation, and unsafe—are proposed to indicate the drone operation status. High-resolution CFD models of urban wind environments in a real city area are coupled with meteorological wind data to provide statistical results for the three indices. The Reynolds-averaged Navier–Stokes turbulence model is employed to simulate two wind environments, standard wind and strong wind, under 36 incoming flow directions. Considering eight flight orientations of drone operating in horizontal planes at various heights, a set of maps for the occurrence probability of the three hazardous indices is provided. These maps can be utilized to determine safe areas, identify no-fly zones corresponding to high occurrence probabilities of deviation and unsafe indices, and establish efficient flight paths for drone operations.