Preflight planning for large-scale Unmanned Aerial Vehicle (UAV) fleets in dynamic, shared airspace presents significant challenges, including temporal No-Fly Zones (NFZs), heterogeneous vehicle profiles, and strict delivery deadlines. While Multi-Agent Path Finding (MAPF) provides a formal framework, existing methods often lack the scalability and flexibility required for real-world Unmanned Traffic Management (UTM). We propose DTAPP-IICR: a Delivery-Time Aware Prioritized Planning method with Incremental and Iterative Conflict Resolution. Our framework first generates an initial solution by prioritizing missions based on urgency. Secondly, it computes roundtrip trajectories using SFIPP-ST, a novel 4D single-agent planner (Safe Flight Interval Path Planning with Soft and Temporal Constraints). SFIPP-ST handles heterogeneous UAVs, strictly enforces temporal NFZs, and models inter-agent conflicts as soft constraints. Subsequently, an iterative Large Neighborhood Search, guided by a geometric conflict graph, efficiently resolves any residual conflicts. A completeness-preserving directional pruning technique further accelerates the 3D search. On benchmarks with temporal NFZs, DTAPP-IICR achieves near-100% success with fleets of up to 1,000 UAVs and gains up to 50% runtime reduction from pruning, outperforming batch Enhanced Conflict-Based Search in the UTM context. Scaling successfully in realistic city-scale operations where other priority-based methods fail even at moderate deployments, DTAPP-IICR is positioned as a practical and scalable solution for preflight planning in dense, dynamic urban airspace.

翻译：在动态共享空域中为大规模无人机集群进行飞行前规划面临诸多严峻挑战，包括临时禁飞区、异构飞行器性能参数以及严格的交付截止时间。尽管多智能体路径规划提供了一个形式化框架，但现有方法通常缺乏实际无人交通管理所需的可扩展性和灵活性。我们提出DTAPP-IICR：一种具有增量迭代冲突解决机制的交付时间感知优先级规划方法。该框架首先根据任务紧急程度确定优先级以生成初始解；其次，采用新型四维单智能体规划器SFIPP-ST（具有软约束与时间约束的安全飞行间隔路径规划）计算往返轨迹。SFIPP-ST能够处理异构无人机，严格强制执行临时禁飞区，并将智能体间冲突建模为软约束。随后，通过几何冲突图引导的迭代大邻域搜索，高效解决所有残留冲突。一种保持完备性的定向剪枝技术进一步加速了三维搜索过程。在包含临时禁飞区的基准测试中，DTAPP-IICR对多达1000架无人机的集群实现了接近100%的成功率，并通过剪枝技术获得高达50%的运行时间缩减，在UTM场景中优于批处理增强型基于冲突的搜索方法。在城市尺度的实际运营场景中，当其他基于优先级的方法在中等规模部署下即告失效时，DTAPP-IICR仍能成功扩展，这使其成为密集动态城市空域中兼具实用性与可扩展性的飞行前规划解决方案。