Prediction of bus passenger trip flow based on artificial neural network

The bus passenger trip flow is the base data for transit route design and optimization, and the characteristic of urban land use is the important factor for transit trip. However, the standard land use data are difficult to reflect the intensity of transit trip. This research proposed a method based on each zone building, land use situation, and bus accessibility to forecast the bus passenger trip flow in future period. Traffic zone is divided into three categories in accordance with the purpose of the residents travel: residential, commercial, and industrial. Then, by artificial neural network model, the three categories of the traffic zone bus passenger trip flow are forecasted. The method is assessed with the data of Dalian developing zone in China and results show its feasibility and reliability. Finally, the future research direction is discussed.