Large-scale integrated passenger transportation hubs are places where multiple modes of transportation are used to switch within the city, and they are also the convergence points of traffic inside and outside the city, and it is important to ensure their smooth under different traffic conditions. Firstly, the passenger travel utility in hubs model and transportation system utility model are proposed; then the travel demands of various types of passengers are accurately identified based on data mining and user portrait technology when the passenger volume is low, and the typical user priority filtering recommendation algorithm and information dynamic update strategy are proposed with the goal of optimal passenger travel utility; then for the large passenger volume scenario, the optimal transportation system operation utility is the goal for us, as the passenger volume increases continuously, the transportation system service is close to the critical state, a bi-level optimization model is established to avoid the resonance of the transportation system and guarantee the balance of optimal utility between the passenger side and the transportation system side. After the internal test of ‘Smooth Hongqiao’ APP, the travel time of passengers in the hub reduced by 5.6%, the utility value of the travel chain increased by 16%, and the saturation of the surrounding road network reduced by 5.7% after the above methods are flexibly applied to build the passenger travel chain according to different traffic scenarios.