arXiv:2607.00064v1 Announce Type: new 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 Contro
The increasing complexity of air traffic and advancements in AI path-planning algorithms are creating a critical need for efficient and interpretable solutions in air traffic management.
This development represents a step towards automating critical infrastructure control, which could significantly improve efficiency and safety in air travel, impacting global logistics and economic activity.
The focus is shifting from purely algorithmic design to algorithms that prioritize human-centered design for controllers, enabling better integration of AI into operational workflows.
- · Air traffic control providers
- · Aviation industry
- · AI software developers
- · Aerospace manufacturers
- · Traditional air traffic management systems
- · Airports with high manual overhead
More efficient and safer air traffic management through AI-powered decision support.
Reduced flight delays and fuel consumption, leading to economic benefits and lower emissions.
Potential for increased air traffic capacity and the enabling of new forms of air mobility (e.g., eVTOL) as airspace management becomes more sophisticated.
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Read at arXiv cs.AI