Safety risk assessment and three-dimensional path planning for UAV in complex urban low-altitude airspace
To meet the pressing need for improved safety and efficiency of low-altitude Unmanned Aerial Vehicle(UAV)flights in complex urban environments,a method for complex urban low-altitude UAV safety risk assessment and three-dimensional(3D)path planning is proposed.Firstly,based on a hierarchical structure of origin/destination/warning boundaries,UAV out-of-bounds conflict rate and buffer airspace occupancy ratio indicators are designed.An optimization model for UAV geofence safety buffer distance is established,and the optimal buffer distance of 28.90 m is scientifically calibrated,serving as the basis for setting the optimal grid granularity of 30 m for the low-altitude airspace.Then,a UAV risk map consisting of a population density layer,sheltered layer,and obstacle layer is constructed.A risk-to-ground assessment model for UAVs is established for two descent modes:ballistic descent and uncontrolled glide,generating a fine-grained and composite urban low-altitude probability risk map.Finally,initial planning,optimization reconstruction,and simulation experiments are conducted for UAV 3D path utilizing geofences,probability risk map,and Jump Point Search algorithm.The effectiveness of the 3 D path planning method is verified,and the parameter sensitivity of the path planning model is analyzed.Experimental results demonstrate that the casualty risk of fixed-wing UAVs is 3 to 50 times higher than that of rotary-wing UAVs,and the casualty risk of ballistic descent mode is 5 to 75 times higher than that of uncontrolled glide de-scent mode.Compared to the A*algorithm,the Jump Point Search algorithm effectively reduces the number of turns and solution time for flight paths,making it more suitable for planning UAV flight paths.Compared to the method without a risk map,UAV path planning based on a risk map reduces 50％of high-risk nodes,with an increase in path length of only 7.2％and 11.4％.The overall casualty risk of path nodes is significantly reduced,effectively ensuring the safety of UAV operations and demonstrating significant effectiveness in executing long-distance missions.The research findings provide a theoretical basis and methodological support for the formulation of flight plans and safety operation supervision for complex urban low-altitude UAV flights.
safety systematicsurban low-altitudeUnmanned Aerial Vehicle(UAV)geofencesafety assessmentpath planningJump Point Search algorithm
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