Researchers are exploring the use of large language models (LLMs) for enhancing safety in air traffic control (ATC) and around non-towered airports. One study proposes a vision-language model approach to analyze radio communications, weather data, and flight trajectories for safety assessments, achieving high F1 scores with open-source models. Another paper introduces a safety-oriented evaluation framework that highlights the critical need for consequence-aware metrics, as standard accuracy measures can mask severe risks in ATC operations. AI
IMPACT LLM analysis could improve safety and efficiency in critical air traffic control operations.
RANK_REASON Two arXiv papers proposing and evaluating LLM-based systems for air traffic safety.
- Air Traffic Control
- Automatic Dependent Surveillance-Broadcast
- Claude Sonnet 4.6
- Common Traffic Advisory Frequency
- Gemini 2.5 Pro
- Gemma-2-9B
- GPT-4o
- GPT-5.4
- Large Language Models
- Mistral-7B
- Non-towered airports
- Qwen 2.5-7B
- Half Moon Bay Airport
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