🤖 AI Summary
This study addresses the challenge of safeguarding high-priority trajectories—such as emergency flights—from interference while maintaining safe separation across a multi-aircraft fleet. The authors propose the Plan-and-Avoid (PAA) framework, which uniquely integrates priority trajectory protection with real-time, uncertainty-aware multi-agent collision avoidance. Leveraging ADS-B data for conflict prediction, PAA generates unilateral maneuver commands that respect aircraft dynamics and comply with RTCA DO-365 standards. Evaluated over more than 140 hours of simulation encompassing over 900 emergency descent scenarios, the system successfully produced feasible resolution advisories for 575 conflicts, achieving end-to-end response times of up to 5.7 seconds and meeting the 35-second collision-avoidance threshold in 93.5% of cases, thereby demonstrating robust end-to-end automated coordination capability.
📝 Abstract
This paper presents a real-time Plan-and-Avoid (PAA framework for coordinating cooperative multi-agent airspace operations around a declared priority trajectory. The priority trajectory represents an aircraft flight plan that must be preserved because of constrained maneuverability, an emergency, a mission-critical task, or assigned operational priority. The framework predicts uncertainty-aware, well-clear separation violations with surrounding traffic and, when the priority plan alone cannot maintain separation, generates vehicle-constrained unilateral advisories that modify nearby aircraft trajectories to maintain well-clear separation for all traffic. The approach is applicable to any declared priority trajectory. This paper demonstrates the Plan component using a contingency landing planner to generate candidate priority trajectories. PAA then identifies nearby aircraft passing too close to this priority trajectory and issues Avoid resolution advisories to these aircraft. The framework is tested using real-world Automatic Dependent Surveillance-Broadcast (ADS-B) traffic from the Washington, D.C., airspace across more than 900 forced-landing cases, totaling over 140 hours of simulated flight. The PAA framework generates feasible cooperative advisories for all 575 unique conflict encounters, with a worst-case end-to-end response time of 5.7 s on a personal computer, including priority trajectory planning, advisory generation, and 1 s two-way datalink delay. In total, 93.5% of generated advisories satisfy the 35 s RTCA DO-365 Detect-and-Avoid temporal threshold. These results demonstrate low-latency coordination for preserving priority trajectories while maintaining well-clear separation through real-time automated advisory generation. Future work will quantify advisory-induced delays and their operational impacts.