Passenger flow distribution forecasting at integrated transport hub via group evolution mechanism and multimodal data

Key Points

• Passenger flow distribution forecasting aids in optimizing traffic at transport hubs, enhancing efficiency.
• A correlation was noted between multimodal data integration and accurate forecasting outcomes.
• Using machine learning techniques and an evolution mechanism ensured adaptability in forecasting models.
• Findings may enable better resource allocation and improved passenger experience at transport hubs.