VIVAERO AI system developed to help prevent airport collisions Near misses like the one at New York's John F. Kennedy International Airport inspired a group from the AirLab in Carnegie Mellon University 's Robotics Institute (RI) to create World2Rules , an AI system that learns interpretable safety rules from data to analyze, verify, and explain potential collision scenarios. By learning from both everyday airport activity and documented safety violations, the system builds a clear picture of what "normal" and "unsafe" behaviors look like. When it detects a potential violation, the system does more than just raise an alert. It identifies which safety rule is being broken and explains why the situation is risky, showing how the scenario matches known patterns of danger rather than issuing a vague warning. "The overall idea we've been working on with this project is to see how we can improve safety in the aviation domain or other safety-critical dom...
