Integrating wind field analysis in UAV path planning: Enhancing safety and energy efficiency for urban logistics
R. Y. Gu, Yifei Zhao, Xinhui Ren
Abstract
Shenzhen, a major city in southern China, has experienced rapid advancements in Unmanned Aerial Vehicle (UAV) technology, resulting in extensive logistics networks with thousands of daily flights. However, frequent disruptions due to its subtropical monsoon climate, including typhoons and gusty winds, present ongoing challenges. Despite the growing focus on operational costs and third-party risks, research on low-altitude urban wind fields remains scarce. This study addresses this gap by integrating wind field analysis into UAV path planning, introducing key innovations to the classical model. First, UAV wind resistance and turbulence constraints are analyzed, mapping high-wind-speed and turbulence-prone zones in the airspace. Second, wind dynamics are incorporated into path planning by considering airspeed and groundspeed variation, optimizing waypoint selection and flight speed adjustments to improve overall energy efficiency. Additionally, a wind-aware Theta* algorithm is proposed, leveraging wind vectors to expedite search process, while Computational Fluid Dynamics (CFD) techniques are employed to calculate wind fields. A case study of Shenzhen, examining wind patterns over the past decade, demonstrates a 6.23% improvement in groundspeed and a 7.69% reduction in energy consumption compared to wind-agnostic models. This framework advances UAV logistics by enhancing route safety and energy efficiency, contributing to more cost-effective operations.