TTR-based framework enables safe, fair, efficient drone coordination

As urban airspace prepares for a surge in drone taxis, delivery drones, and air taxis, researchers at multiple institutions (Low, Aloor, Tuck, Nuzzo, Choi) introduce a novel coordination framework built around minimum time-to-reach (TTR). The key insight: TTR—the shortest time a vehicle can reach a given point—serves as a single, unified metric to assign priorities, enforce temporal separation, and filter unsafe actions. When multiple aerial vehicles need to merge into an air corridor, the system assigns each a priority based on its TTR to the merge point, then uses target TTR values to space them out in time, naturally creating spatial separation. A safety filter based on Hamilton-Jacobi reachability value functions then intervenes only when necessary to prevent collisions, minimally overriding the reference guidance.

Simulation results in a highly congested corridor merging scenario show that this TTR-based approach outperforms both time-optimal guidance (which ignores fairness and safety) and priority-agnostic safety filtering. The framework improves safety by avoiding collisions more consistently, fairness by distributing delays more equitably, and efficiency by minimizing total travel time deviations. While the paper focuses on aerial vehicles, the same principles could apply to autonomous ground vehicles, marine vessels, or any multi-agent coordination problem requiring safe, fair, and efficient merging. The work is submitted to the 65th IEEE Conference on Decision and Control (2026) and is available on arXiv.