The PRELUDE project, conducted within Eurocontrol’s Air Transport Innovation Network (EATIN), investigates data-driven approaches to enhance the passenger experience at luggage reclaim. Supported by 14 airports and three major airlines, the project applies machine learning to operational datasets to predict first and last bag arrival times. Surveys across multiple European airports reveal that over 80% of passengers would value predictions of luggage delivery. Preliminary results demonstrate high predictive accuracy and strong potential to improve passenger satisfaction. Düsseldorf Airport actively collaborates on the project, supporting the operational validation and exploring model integration as a key step toward scalability across European airports.

• Machine learning predictions of luggage delivery time at airport reclaim areas
• Passenger surveys capturing current passenger needs and preferences
• Quantile machine learning as an approach to overestimate model predictions