Due to the features of high speed and large capacity, the airport express becomes a main transportation mode feeding to the airports that locate far away from downtown. This study firstly takes the airport express as the research object and analyzes the influence factors of airport express passenger demand. Then considering the impact of the urban public and rail transit network on the passenger demand of the airport express, this study constructed the BP neural network model based on GA for prediction under specific routes, taking ground bus connection time, transfer times, travel time, travel cost, public transportation accessibility as input variables and airport express passenger demand production rate as output variables. Finally, this study takes the Beijing Capital International Airport as an example to verify the model and analyze the importance of the influence factors using IC card data and cell phone data.

CICTP