Research on Flight Conflict Resolution Method for UAV Based on a Modified Sparrow Search Algorithm

To enhance aviation safety by preventing mid-air accidents between UAVs and conventional aircraft, this study introduces an enhanced Sparrow Search Algorithm (SSA) framework for aerial vehicle conflict management. The research initially formulates UAV collision avoidance as a multi-constraint optimization model, addressing both spatial separation requirements and operational limitations. Recognizing the inherent limitations of conventional SSA in global search capabilities, we implement strategic improvements to its exploration mechanism through the dynamic parameter adaptation. Subsequent computation experiments demonstrate the refined algorithm's superior performance in computational efficiency and operational effectiveness compared to baseline methods. These quantitative outcomes substantiate the technical viability of employing optimized swarm intelligence approaches for resolving complex airspace coordination challenges in unmanned aerial systems.