发表机构
Delft University of Technology（代尔夫特理工大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
提出一种基于解空间的冲突避免路径规划算法，集成三种意图冲突检测方法，通过顶点和边搜索节点实现高效计算，在MUAC Delta扇区测试中平均计算时间3.69毫秒。
AI 中文摘要
随着技术进步，许多路径规划算法已被提出用于空中交通管理，但它们在战术控制中的操作采用仍然有限，揭示了算法设计优先级与空中交通管制员需求之间的错位。这突显了对本质上可解释、计算高效且明确为人类使用而设计的决策支持解决方案的需求。聚焦于这一设计挑战，本研究开发了一种用于航路空中交通管制（ATC）的无冲突路径规划算法，旨在与两个指导性考虑兼容：（1）解空间显示提供的可解释性和灵活性，这促使构建一个暴露所有可行安全动作并适应不断变化的优化目标的算法；（2）管制员在强制执行操作约束（如间隔标准、机动性限制、航路点最小化和路由实用性）时自然应用的决策逻辑。以这些原则为中心，该算法在解空间框架内集成了三种基于意图的冲突检测方法——基于距离、基于时间间隔和基于区域——以计算高效的方式识别无冲突路径。此外，提出了基于顶点和基于边的搜索节点用于解空间路径规划（SSPP），分别产生两个变体——SSPPV和SSPPE，并在计算速度和解决方案质量方面进行评估。实证结果表明，SSPPV与基于区域的冲突检测相结合实现了最佳性能，在基于马斯特里赫特高空区域管制中心（MUAC）Delta扇区的操作相关场景中，使用5海里网格，平均计算路径时间为3.69毫秒。
英文摘要
As technology advances, various algorithms have been proposed for air traffic management, yet their operational adoption in tactical control remains limited. This gap motivates a human-centered design emphasizing algorithmic interpretability, controller-relevant operational constraints, and real-time computation. Inspired by the interpretability and flexibility of solution-space displays, as well as by the decision logic controllers naturally apply when enforcing operational constraints, this study extends the solution-space concept to path planning and develops a fast conflict-free path-planning algorithm for en-route Air Traffic Control (ATC), termed Solution Space Path Planning (SSPP). The algorithm integrates three intent-based conflict detection methods---distance-based, time-interval-based, and zone-based---within the solution-space framework to identify conflict-free paths in computationally efficient ways. SSPP is developed using both vertex-based and edge-based search nodes, resulting in two variants---SSPPV and SSPPE, respectively. Empirical results show that SSPPV paired with zone-based conflict detection performs best, computing paths in 3.69 ms on average in the Dutch Delta sector using a 5 nmi grid. SSPPV remains approximately 3.77 times faster than SSPPE while offering competitive effectiveness, making it suitable for time-critical operations and interactive 'what-if' probing in real time. An extension to SSPPV and SSPPE further examines the trade-off between delay minimization and separation requirements, demonstrating the flexibility of SSPP in revising optimization objectives. This study not only proposes a novel path-planning algorithm but also shows how such algorithms can be designed to align with human use and operational requirements, supporting their integration into future ATC systems.
Comments37 pages, 16 figures
