Simulation of Passenger Flow Distribution and Transport Capacity Dispatching for Integrated Hubs

Due to complex layouts and multimodal passenger interactions of integrated transport hubs, it is prone to issues of slow evacuation and elevated risks. Consequently, accelerating passenger circulation and improving vehicle utilization have become critical challenges. However, effectively reducing hub congestion through optimized vehicle scheduling remains a highly complex problem. This study first establishes a macroscopic reservoir model for hubs with passenger inflows and outflows to predict the converging multimodal passenger demand. With the goal of minimizing hub load intensity, a train–passenger coupling model for urban rail transit is developed to estimate the required transport capacity. Then, from a micro perspective, a path multi-node graph network is constructed based on the hub’s digital twin model. It provides assistance through the identification of passenger accumulation and density on platforms under environmental disturbances, thereby enabling the coordination of train timetables. Finally, a passenger flow simulation model is constructed with the constraint of facility capacity, and an optimization algorithm is proposed, and a customized penalty function is introduced to optimize the density–velocity relationship of passenger-group agents for enhanced efficiency. The trained model captures congestion variations under multiple event scenarios, enabling the perception of hub load changes resulting from management strategies and equipment operating modes. The effectiveness of this approach is tested with a real-world transportation hub dataset and yields a superior scheduling scheme. The experimental results show that high-density rails have the greatest impact on passenger congestion levels, especially during peak hours. The proposed method performs better than using timetable or micro-simulation methods alone. This study is beneficial to the attractiveness of public transportation and to reducing the cost of train usage, while also providing an important theoretical basis and practical insights for operators, thereby promoting the sustainable development of urban transportation systems.