实时规划紧急降落路径，兼顾空域风险与地面安全
Airspace-aware Contingency Landing Planning
- 基于历史飞行数据构建空域模型，动态生成高风险区域热图
- 在2.9秒内完成路径规划，联合降低空域与地面风险
- 适合航空应急管理、无人机调度等需要快速决策的场景
本文提出一种实时、基于搜索的飞机应急降落规划方法，旨在最小化交通中断并考虑地面风险。空域模型整合密集的进出港航班流、直升机走廊和禁飞区，并以华盛顿特区为例进行验证。利用历史自动相关监视广播（ADS-B）数据估算航班密度，通过低延迟计算几何算法生成高风险走廊和受限区域的邻近热图。空域风险定义为降落路径在拥堵区域的累计暴露时间，地面风险则由飞越人口密度评估，共同指导路径选择。落地点选择模块进一步减轻对正常航班运行的干扰。与最小风险的杜宾路径相比，该规划器在保持实时性能的同时实现了更低的综合风险和更小的空域扰动。在仅考虑空域风险条件下，该方法在笔记本电脑上平均耗时2.9秒。未来工作将引入动态空域更新，实现时空协同的应急降落规划，减少对实时流量重绕的需求。
原文摘要 · Abstract (English)
This paper develops a real-time, search-based aircraft contingency landing planner that minimizes traffic disruptions while accounting for ground risk. The airspace model captures dense air traffic departure and arrival flows, helicopter corridors, and prohibited zones and is demonstrated with a Washington, D.C., area case study. Historical Automatic Dependent Surveillance-Broadcast (ADS-B) data are processed to estimate air traffic density. A low-latency computational geometry algorithm generates proximity-based heatmaps around high-risk corridors and restricted regions. Airspace risk is quantified as the cumulative exposure time of a landing trajectory within congested regions, while ground risk is assessed from overflown population density to jointly guide trajectory selection. A landing site selection module further mitigates disruption to nominal air traffic operations. Benchmarking against minimum-risk Dubins solutions demonstrates that the proposed planner achieves lower joint risk and reduced airspace disruption while maintaining real-time performance. Under airspace-risk-only conditions, the planner generates trajectories within an average of 2.9 seconds on a laptop computer. Future work will incorporate dynamic air traffic updates to enable spatiotemporal contingency landing planning that minimizes the need for real-time traffic rerouting.
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