Research on Passenger Demand Prediction for Airport Express

摘要

Due to high speed and large capacity, airport express is a main transportation mode for airports located away from downtown. This study analyzes the influence factors of airport express passenger demand. Considering the impact of the urban rail 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, and 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. The model can be used to guide the route optimization of airport fast track and analyze the passenger flow coverage of airport fast track.