Multi UAVs Preflight Planning in a Shared and Dynamic Airspace

TL;DR

This paper introduces DTAPP-IICR, a scalable preflight planning framework for large UAV fleets in dynamic urban airspace, effectively handling temporal NFZs, heterogeneity, and conflicts to ensure efficient, near-100% success rates.

Contribution

The paper presents a novel planning method combining prioritized mission scheduling, a new 4D planner SFIPP-ST, and conflict resolution techniques, advancing scalability and flexibility in UAV traffic management.

Findings

Achieves near-100% success with up to 1,000 UAVs.

Reduces runtime by up to 50% through pruning.

Outperforms existing batch conflict-based methods in urban scenarios.

Abstract

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.