实时协调空中多机飞行,保障优先航迹安全不冲突。
Plan-and-Avoid: Real-Time Aircraft Trajectory Coordination in a Multi-Agent Environment

- 基于预测与避让的实时框架,动态生成避让建议
- 93.5%建议满足35秒响应标准,最坏延迟仅5.7秒
- 适用于紧急降落等高优先级航迹,支持真实空域测试
本文提出一种实时计划与避让(Plan-and-Avoid, PAA)框架,用于在多智能体空域环境中协调合作飞行,保护具有优先权的航迹。该优先航迹因机动能力受限、应急情况、任务关键性或操作指派而必须保留。框架通过预测周围交通可能造成的安全距离违规,在仅靠优先航迹无法保持安全间隔时,生成受车辆约束的单方面避让建议,调整邻近飞机航迹以确保所有航空器保持充分安全距离。该方法适用于任意声明的优先航迹。本文使用华盛顿特区空域的真实自动相关监视广播(ADS-B)数据,在超过900次强制着陆场景中进行模拟,累计飞行时间超140小时。PAA成功为全部575个独立冲突场景生成可行协作建议,端到端最坏响应时间仅5.7秒(含航迹规划、建议生成及1秒双向数据链延迟)。总共有93.5%的建议满足RTCA DO-365规定的35秒检测与避让时间阈值。结果表明,该框架可在低延迟下实现优先航迹保护与整体安全间隔维持。未来工作将量化建议引发的延误及其运行影响。
原文摘要 · Abstract (English)
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.
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