As the commercial application of drones continues to expand, the traffic volume in low-altitude zones below 400 feet is expected to significantly increase. The research team at Johns Hopkins University has developed a system model using AI to safely manage drone traffic through automated decision-making. They have validated the effectiveness of their autonomous algorithms in a simulated three-dimensional airspace. The results indicate that collision avoidance algorithms and strategy conflict resolution algorithms can greatly reduce the incidence of accidents. The team plans to further refine the simulation environment to incorporate more variables, aiming to achieve efficient and safe operation of drone systems.