Solution space path planning for supporting en-route air traffic control

2026-06-30

AI Summary

Existing air route planning algorithms struggle to simultaneously achieve explainability, computational efficiency, and human–machine collaboration requirements in tactical-level air traffic control. This work proposes a solution-space-based conflict-free path planning framework that integrates air traffic controller decision logic and operational constraints, enabling flexible multi-objective optimization while outputting all feasible and safe maneuvers. The approach innovatively introduces three intent-aware conflict detection mechanisms—based on distance, time intervals, and spatial regions—and designs two types of search node structures: vertex-based (SSPPV) and edge-based (SSPPE). Experimental results demonstrate that, in the MUAC Delta sector under a 5-nautical-mile grid scenario, SSPPV combined with region-based conflict detection generates high-quality, conflict-free trajectories in an average of only 3.69 milliseconds.

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. 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. 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. 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.

Problem

• Air Traffic Control
• Path Planning
• Solution Space
• Conflict Detection
• Human-Centered Design

Innovation

• solution-space path planning
• conflict detection
• air traffic control
• interpretable algorithm
• vertex-based search