Solution space path planning for supporting en-route air traffic control
Solution space path planning for supporting en-route air traffic control
用于支持航路空中交通管制的解空间路径规划
Abstract: As technology advances, many path-planning algorithms have been proposed for Air Traffic Management, yet their operational adoption in tactical control remains limited, revealing a misalignment between algorithmic design priorities and air traffic controllers’ needs. This underscores the need for decision-support solutions that are inherently interpretable, computationally efficient, and explicitly designed for human use.
摘要： 随着技术的进步，许多用于空中交通管理的路径规划算法被提出，但它们在战术管制中的实际应用仍然有限，这揭示了算法设计重点与空中交通管制员需求之间的错位。这凸显了对决策支持解决方案的需求，这些方案必须具备内在的可解释性、计算高效性，并明确为人类使用而设计。
Focusing on this design challenge, this study develops a conflict-free path-planning algorithm for en-route Air Traffic Control (ATC) designed to be compatible with two guiding considerations: (1) the interpretability and flexibility offered by solution-space displays, which motivate constructing an algorithm that exposes all feasible safe actions and accommodates shifting optimization goals; and (2) the decision logic controllers naturally apply when enforcing operational constraints, such as separation standards, maneuverability limits, waypoint minimization, and routing practicality.
针对这一设计挑战，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，旨在兼容两个指导性考量：(1) 解空间显示所提供的可解释性和灵活性，这促使我们构建一种能够展示所有可行安全动作并适应不断变化的优化目标的算法；(2) 管制员在执行运行限制（如间隔标准、机动性限制、航点最小化和航线实用性）时自然应用的决策逻辑。
Centered on these principles, the algorithm integrates three intent-based conflict detection methods — distance-based, time-interval-based, and zone-based — within a solution-space framework to identify conflict-free paths in computationally efficient ways. Additionally, vertex-based and edge-based search nodes are proposed for solution space path planning (SSPP), resulting in two variants — SSPPV and SSPPE, respectively, which are evaluated in terms of computational speed and solution quality.
基于这些原则，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的方法，以高效计算的方式识别无冲突路径。此外，针对解空间路径规划（SSPP）提出了基于顶点和基于边的搜索节点，从而产生了两个变体——SSPPV 和 SSPPE，并分别对它们的计算速度和解质量进行了评估。
Empirical results show that SSPPV paired with zone-based conflict detection achieves the best performance, computing paths in 3.69 ms on average in operational-relevant scenarios based on the Delta sector of the Maastricht Upper Area Control Centre (MUAC) using a 5 nmi grid.
实证结果表明，SSPPV 与基于区域的冲突检测相结合表现最佳，在基于马斯特里赫特高空管制中心（MUAC）Delta 扇区、使用 5 海里网格的运行相关场景中，平均计算路径耗时仅为 3.69 毫秒。