Research on Multi-Airspace Conflict Detection and Resolution Method Based on Octree Spatial Grid Partitioning

With the rapid development of the aviation industry, the complexity and intertwinement of various aviation activities have been continuously increasing, leading to the escalating of potential conflicts in limited airspace resources. Efficient airspace management is crucial for flight safety. To address the issues of conflict detection and resolution in localized high-density multi-airspace environments, this paper proposes an end-to-end integrated framework that integrates octree spatial partitioning, hierarchical conflict detection, and a conflict resolution module based on the Improved Whale Migration Algorithm (IWMA). This framework takes the airspace safety separation standards as constraints and the minimization of multi-airspace adjustment offsets as the optimization objective. The IWMA integrates diverse population structures and multi-strategy optimization technologies to balance global search and local exploration capabilities and avoid falling into local optima. Experiments on high-density conflict scenarios of different scales have verified the effectiveness and robustness of the proposed method. Simulation results show that compared with traditional detection methods and other classic optimization algorithms, the conflict detection and resolution method proposed in this paper can quickly and efficiently provide reliable solutions for multi-airspace conflict issues.