基于系统安全分析的低空无人机冲突检测模型OA

While low-altitude Unmanned Aerial Vehicle(UAV)operations face collision risks in complex environments,traditional fixed separation thresholds have difficulties in adapting to complex meeting scenarios,with excessive thresholds resulting in airspace resource wastes and insufficient thresholds leading to residual collision hazards.This paper introduces system safety analysis methods to identify key risk factors in a UAV Traffic Management(UTM)system,and designs an adaptive dynamic Protected Airspace Zone(PAZ)model that incorporates safety parameters such as speed,acceleration,positioning error,and redundancy distance.Combined with an airspace grid partitioning and layered conflict detection algorithm,this approach enables efficient real-time conflict detection and tiered response for low-altitude UAVs.Experiments in vertical crossing,head-on horizontal and oblique approach,and communication loss scenarios validate the algorithm's effectiveness:all conflicts are resolved with final separations above safety thresholds and a nearly 100%collision avoidance success rate.Monte Carlo simulations further show an average response time of 2.9 s,demonstrating strong robustness and real-time performance.This research provides a novel approach that integrates system safety engineering with conflict detection technology to enhance collision risk management for low-altitude UAVs.