{"id":534,"date":"2025-04-15T12:01:33","date_gmt":"2025-04-15T11:01:33","guid":{"rendered":"https:\/\/research.dblue.it\/trusty\/?p=534"},"modified":"2025-05-06T10:52:47","modified_gmt":"2025-05-06T09:52:47","slug":"trustys-final-validation-experiment-exploring-trust-in-ai-for-remote-digital-towers","status":"publish","type":"post","link":"https:\/\/research.dblue.it\/trusty\/2025\/04\/15\/trustys-final-validation-experiment-exploring-trust-in-ai-for-remote-digital-towers\/","title":{"rendered":"TRUSTY’s Final Validation Experiment: Exploring Trust in AI for Remote Digital Towers"},"content":{"rendered":"

The TRUSTY project has achieved a crucial milestone with the successful completion of its Final Validation Experiment, bringing us one step closer to shaping the future of AI-powered air traffic management.<\/em><\/p>\n

At TRUSTY<\/strong>, we are proud to highlight a significant achievement in our ongoing research. The Final Validation Experiment<\/strong> of the TRUSTY project<\/strong>, part of the SESAR Joint Undertaking<\/strong>, has provided valuable insights into how air traffic controllers (ATCOs)<\/strong> interact with and trust explainable AI systems<\/strong> within Remote Digital Tower (RDT)<\/strong> environments.<\/p>\n

During this validation exercise, held at ENAC\u2019s ACHIL simulation platform<\/strong> in March 2025, 17 expert controllers were tasked with evaluating the transparency and explainability of AI-based systems used in high-stakes air traffic management<\/strong> scenarios. The goal was to understand how these features can foster trust and improve decision-making when managing remote airports under complex operational conditions.<\/p>\n

What Happened in the Experiment?<\/strong><\/h4>\n

The validation exercise took place in two different simulated environments:<\/p>\n

    \n
  1. \n

    Toulouse Blagnac Airport (LFBO)<\/strong>
    Controllers managed air traffic operations like pushback, taxiing, and takeoffs via radio communication<\/strong> with pilots.<\/p>\n<\/li>\n

  2. \n

    Muret-Lherm Aerodrome (LFBR)<\/strong>
    Here, controllers supervised operations remotely using AI-assisted event detection<\/strong> (video and audio) but without direct communication with pilots<\/strong>, giving valuable insights into AI\u2019s role in supporting decision-making without the need for direct human-pilot interaction.<\/p>\n<\/li>\n<\/ol>\n

    Why is this Experiment Important?<\/strong><\/h4>\n

    The outcomes from this experiment will guide the development of trustworthy AI systems<\/strong> for future Remote Digital Tower operations<\/strong>, in full alignment with EASA\u2019s<\/strong> regulatory guidelines. The focus on transparency<\/strong> and explainability<\/strong> will ensure that AI systems are reliable, effective, and trustworthy for air traffic controllers working in dynamic and high-pressure environments.<\/p>\n

    At TRUSTY<\/strong>, we are committed to driving forward the future of AI in aviation<\/strong>. By continuing our research, experimentation, and validation of AI-based solutions for remote towers, we aim to improve the human-AI interaction<\/strong> and refine transparency in air traffic management systems.<\/p>\n

    What\u2019s Next?<\/strong><\/h4>\n

    As we continue to explore and refine our findings, we look forward to sharing more updates on the progress of the TRUSTY project. These discoveries will play an essential role in developing safer, smarter, and more efficient air traffic management systems in Remote Digital Towers<\/strong>.<\/p>\n

    Stay connected and explore more about the project below:<\/p>\n