{"id":503,"date":"2026-10-05T12:48:18","date_gmt":"2026-10-05T11:48:18","guid":{"rendered":"https:\/\/research.dblue.it\/tada\/?p=503"},"modified":"2026-10-05T14:56:27","modified_gmt":"2026-10-05T13:56:27","slug":"validating-digital-technology-for-atm-insights-from-the-tada-aware-orci-joint-open-day","status":"publish","type":"post","link":"https:\/\/research.dblue.it\/tada\/2026\/10\/05\/validating-digital-technology-for-atm-insights-from-the-tada-aware-orci-joint-open-day\/","title":{"rendered":"Validating Digital Technology for ATM: Insights from the TADA, AWARE &#038; ORCI Joint Open Day"},"content":{"rendered":"<p style=\"text-align: justify;\">On September 30th, the TADA project joined forces with our <a href=\"https:\/\/www.sesarju.eu\/\">SESAR JU<\/a> sister projects, <a href=\"https:\/\/www.aware-sesar.eu\/\">AWARE<\/a> and <a href=\"https:\/\/orci.isa-software.com\/\">ORCI<\/a>, to host an <strong>online <a href=\"https:\/\/research.dblue.it\/tada\/2026\/09\/10\/digital-air-traffic-management-tada-aware-orci-joint-open-day\/\" target=\"_blank\" rel=\"noopener\">Joint Open Day<\/a><\/strong>. Bringing together aviation professionals, researchers, and active Air Traffic Controllers (ATCOs), the event showcased the progress of <strong>Artificial Intelligence and automation in Air Traffic Management<\/strong>. During the event, the interactive panel and live demonstrations highlighted a shared vision: AI purpose is to empower human controllers, supporting the mitigation of cognitive overload in increasingly complex airspaces.<\/p>\n<h3>A 360\u00b0 View of the Flight Profile<\/h3>\n<p style=\"text-align: justify;\" data-path-to-node=\"3\">In fact, the strength of this joint event was the opportunity to present a <strong>complete, sequential look at how AI supports operations<\/strong> across the entire flight path.<\/p>\n<ul data-path-to-node=\"4\">\n<li>\n<p id=\"p-rc_1351a9ec2585bdbc-78\" style=\"text-align: justify;\" data-path-to-node=\"4,0,0\"><span data-path-to-node=\"4,0,0,0\"><b data-path-to-node=\"4,0,0,0\" data-index-in-node=\"0\"><a href=\"https:\/\/www.aware-sesar.eu\/index.html#first\" target=\"_blank\" rel=\"noopener\">AWARE (En-route)<\/a>:<\/b> Validated in Malm\u00f6 ATC, AWARE focuses on the en-route phase by developing an enhanced Artificial Situational Awareness (ASA) system<\/span><span data-path-to-node=\"4,0,0,2\">. By integrating knowledge-graph reasoning and Machine Learning, the system assesses ATCO goals and suggests support actions while ensuring the controller retains ultimate control<\/span><span data-path-to-node=\"4,0,0,4\">.<\/span><\/p>\n<\/li>\n<li>\n<p id=\"p-rc_1351a9ec2585bdbc-79\" style=\"text-align: justify;\" data-path-to-node=\"4,1,0\"><span data-path-to-node=\"4,1,0,0\"><b data-path-to-node=\"4,1,0,0\" data-index-in-node=\"0\">TADA (Terminal Manoeuvring Area):<\/b> Focused on the Milano TMA (Malpensa and Bergamo), TADA provides a digital assistant that translates AMAN sequences into separated, proposed 4D trajectories (4DPT), giving controllers a clear indication of distance-to-go and decision-making support<\/span><span data-path-to-node=\"4,1,0,2\">.<\/span><\/p>\n<\/li>\n<li>\n<p id=\"p-rc_1351a9ec2585bdbc-80\" style=\"text-align: justify;\" data-path-to-node=\"4,2,0\"><span data-path-to-node=\"4,2,0,0\"><b data-path-to-node=\"4,2,0,0\" data-index-in-node=\"0\"><a href=\"https:\/\/orci.isa-software.com\/aboutorci\/\" target=\"_blank\" rel=\"noopener\">ORCI (Final Approach)<\/a>:<\/b> Handling the critical final approach phase, ORCI utilises an AI-based Decision Support Tool (DST) to predict spacing between consecutive aircraft at the localiser interception point<\/span><span data-path-to-node=\"4,2,0,2\">. Specifically, this concept has been successfully validated in Barcelona and Lisbon to improve arrival spacing predictability<\/span><span data-path-to-node=\"4,2,0,4\">.<\/span><\/p>\n<\/li>\n<\/ul>\n<h3>The TADA Solution in the Terminal Airspace<\/h3>\n<p><img decoding=\"async\" class=\"aligncenter wp-image-519 size-large\" src=\"https:\/\/research.dblue.it\/tada\/wp-content\/uploads\/sites\/23\/2026\/10\/TADA_scope-overview-1024x538.png\" alt=\"\" width=\"1024\" height=\"538\" srcset=\"https:\/\/research.dblue.it\/tada\/wp-content\/uploads\/sites\/23\/2026\/10\/TADA_scope-overview-200x105.png 200w, https:\/\/research.dblue.it\/tada\/wp-content\/uploads\/sites\/23\/2026\/10\/TADA_scope-overview-300x158.png 300w, https:\/\/research.dblue.it\/tada\/wp-content\/uploads\/sites\/23\/2026\/10\/TADA_scope-overview-400x210.png 400w, https:\/\/research.dblue.it\/tada\/wp-content\/uploads\/sites\/23\/2026\/10\/TADA_scope-overview-600x315.png 600w, https:\/\/research.dblue.it\/tada\/wp-content\/uploads\/sites\/23\/2026\/10\/TADA_scope-overview-768x404.png 768w, https:\/\/research.dblue.it\/tada\/wp-content\/uploads\/sites\/23\/2026\/10\/TADA_scope-overview-800x421.png 800w, https:\/\/research.dblue.it\/tada\/wp-content\/uploads\/sites\/23\/2026\/10\/TADA_scope-overview-1024x538.png 1024w, https:\/\/research.dblue.it\/tada\/wp-content\/uploads\/sites\/23\/2026\/10\/TADA_scope-overview-1200x631.png 1200w, https:\/\/research.dblue.it\/tada\/wp-content\/uploads\/sites\/23\/2026\/10\/TADA_scope-overview-1536x808.png 1536w, https:\/\/research.dblue.it\/tada\/wp-content\/uploads\/sites\/23\/2026\/10\/TADA_scope-overview.png 1668w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/p>\n<p id=\"p-rc_1351a9ec2585bdbc-81\" style=\"text-align: justify;\" data-path-to-node=\"6\"><span data-path-to-node=\"6,0\">Within this broader ATM ecosystem, TADA tackles the tactical <a href=\"https:\/\/research.dblue.it\/tada\/about\/\" target=\"_blank\" rel=\"noopener\"><strong>challenges of a busy Terminal Manoeuvring Area<\/strong><\/a>. To achieve this, TADA leverages a multi-agent Reinforcement Learning (RL) architecture<\/span><span data-path-to-node=\"6,2\">. This advanced system learns to issue discrete operational clearances to individual aircraft, which preserves necessary separation, reduces schedule deviation, and limits unnecessary controller interventions<\/span><span data-path-to-node=\"6,4\">.<\/span><\/p>\n<p id=\"p-rc_1351a9ec2585bdbc-82\" style=\"text-align: justify;\" data-path-to-node=\"7\"><span data-path-to-node=\"7,0\">Ultimately, TADA aims to deliver an intelligent <a href=\"https:\/\/research.dblue.it\/tada\/2025\/04\/18\/navigating-busy-airport-operations-with-ai-tada-digital-assistant\/\" target=\"_blank\" rel=\"noopener\">Digital Assistant<\/a> and an optimised Human-Machine Interface (HMI) that supports ATCO decision-making and reduces workload. At the same time, the TADA solution will improve airspace capacity, enhancing safety, and enabling more efficient flight trajectories<\/span><span data-path-to-node=\"7,2\">.<\/span><\/p>\n<h3 data-path-to-node=\"8\">Key Takeaways from the Joint Panel<\/h3>\n<p style=\"text-align: justify;\" data-path-to-node=\"9\">The panel discussion highlighted practical insights regarding the operational deployment of Human-AI teaming in aviation. Below, some of the key takeaways from the joint Open Day panel discussion.<\/p>\n<ul data-path-to-node=\"10\">\n<li style=\"text-align: justify;\">\n<p id=\"p-rc_1351a9ec2585bdbc-83\" data-path-to-node=\"10,0,0\"><span data-path-to-node=\"10,0,0,0\"><b data-path-to-node=\"10,0,0,0\" data-index-in-node=\"0\">AI as a Safety Net:<\/b> Automated tools come in handy for monitoring probabilistic events (like conflict detection) and reliably performing monotonous tasks, acting as a robust additional safety layer for controllers<\/span><span data-path-to-node=\"10,0,0,2\">.<\/span><\/p>\n<\/li>\n<li style=\"text-align: justify;\">\n<p id=\"p-rc_1351a9ec2585bdbc-84\" data-path-to-node=\"10,1,0\"><span data-path-to-node=\"10,1,0,0\"><b data-path-to-node=\"10,1,0,0\" data-index-in-node=\"0\">Retaining Human Authority:<\/b> Across all three projects, a central tenet remains clear: whether using linear regression models, multi-agent reinforcement learning, or knowledge graphs, the technology is designed to support decision-making while explicitly retaining ATCO control<\/span><span data-path-to-node=\"10,1,0,2\">.<\/span><\/p>\n<\/li>\n<li>\n<p id=\"p-rc_1351a9ec2585bdbc-85\" style=\"text-align: justify;\" data-path-to-node=\"10,2,0\"><span data-path-to-node=\"10,2,0,0\"><b data-path-to-node=\"10,2,0,0\" data-index-in-node=\"0\">Sustainability and Efficiency:<\/b> Smarter automation directly supports environmental sustainability by optimizing resource usage and reducing unnecessary emissions, all while driving up overall sector capacity<\/span><span data-path-to-node=\"10,2,0,2\">.<\/span><\/p>\n<\/li>\n<\/ul>\n<h3 data-path-to-node=\"11\">Access the Event Materials<\/h3>\n<p data-path-to-node=\"12\">Did you miss the live session or want to revisit a specific technical demonstration? The Open Day presentation slide decks from TADA, AWARE, and ORCI will be available here shortly! So, don&#8217;t miss out on the joint Open Day materials and check the TADA News page to keep updated.<\/p>\n<ul>\n<li data-path-to-node=\"12\"><a href=\"https:\/\/research.dblue.it\/tada\/?sdm_process_download=1&amp;download_id=515\" target=\"_blank\" rel=\"noopener\">TADA Project presentation<\/a><\/li>\n<li data-path-to-node=\"12\">AWARE Project presentation<\/li>\n<li data-path-to-node=\"12\">ORCI Project presentation<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>On September 30th, the TADA project joined forces with our  [&#8230;]<\/p>\n","protected":false},"author":21,"featured_media":507,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-503","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorised"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.6 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>AWARE, ORCI &amp; 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