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LLMs evaluated for air traffic safety analysis

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

Summary written by gemini-2.5-flash-lite from 2 sources. How we write summaries →

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.

Read on arXiv cs.CL →

COVERAGE [2]

  1. arXiv cs.AI TIER_1 · Peng Wei ·

    Towards Automated Air Traffic Safety Assessment Around Non-Towered Airports Using Large Language Models

    We investigate frameworks for post-flight safety analysis at non-towered airports using large language models (LLMs). Non-towered airports rely on the Common Traffic Advisory Frequency (CTAF) for air traffic coordination and experience frequent near mid-air collisions due to the …

  2. arXiv cs.CL TIER_1 · Sameer Alam ·

    Safety-Oriented Evaluation of Language Understanding Systems for Air Traffic Control

    Air Traffic Control (ATC) is a safety-critical domain in which incorrect interpretation of instructions may lead to severe operational consequences. While large language models (LLMs) demonstrate strong general performance, their reliability in operational ATC environments remain…