# Solution Space Path Planning: A Real-Time Human-Centered Path Planning Algorithm for En-Route Air Traffic Control

arXiv: https://arxiv.org/abs/2607.00064 · HTML: https://mlsanity.com/paper/2607.00064/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 8 of its 81 references that are in the map.
- First posted on arXiv 30 Jun 2026.

## Builds on (most cited first, 8 of 8)

- [Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI](https://mlsanity.com/paper/1910.10045/) (2019)
- [Theta*: Any-Angle Path Planning on Grids](https://mlsanity.com/paper/1401.3843/) (2014)
- [Any-Angle Pathfinding for Multiple Agents Based on SIPP Algorithm](https://mlsanity.com/paper/1703.04159/) (2017)
- [Non-Uniform Interpolation in Integrated Gradients for Low-Latency Explainable-AI](https://mlsanity.com/paper/2302.11107/) (2023)
- [Towards Time-Optimal Any-Angle Path Planning With Dynamic Obstacles](https://mlsanity.com/paper/2104.06681/) (2021)
- [Conflict-Free Four-Dimensional Path Planning for Urban Air Mobility Considering Airspace Occupations](https://mlsanity.com/paper/2107.12829/) (2021)
- [Path Planning in Dynamic Environments with Adaptive Dimensionality](https://mlsanity.com/paper/1605.06853/) (2016)
- [Optimal and Bounded Suboptimal Any-Angle Multi-agent Pathfinding](https://mlsanity.com/paper/2404.16379/) (2024)

## Abstract (arXiv)

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.