Airport Terminal Passenger Queue Forecasting for Departure Gates and Security Checkpoints
Researchers have developed a new framework for forecasting passenger queues at airport departure gates and security checkpoints. The model utilizes a Transformer-based architecture to analyze historical passenger flow data, capturing temporal dependencies and correlations between different airport facilities. This approach aims to provide accurate forecasts up to two hours in advance, enabling proactive management of congestion and staff allocation. AI
IMPACT Provides a novel method for improving operational efficiency in transportation hubs through AI-driven predictions.