Abstract: Data fusion method is used to obtain the individual travel information of bus and subway passengers before and after the opening of the new subway line. The important human mobility index, center of mass, is used to locate the center of mass of passengers’ bus boarding locations, and the impact of the distance between a subway station and the center of mass on passengers’ choice of subway stations is analyzed. Results show that 86.15% of the passengers choose subway stations closer to their center of mass, and the distance is a key factor affecting passengers’ station choice behavior. Based on the findings above, we develop a Logit model to predict whether a passenger will choose to use the new subway station. The prediction accuracy, precision, recall and specificity are 83.87%, 84.23%, 83.66% and 84.09%, respectively, indicating that the model performs well. The results of this study can be used to evaluate the impact of planned new subway stations on the adjacent existing subway stations and contribute to the design of subway operation plan.