The prediction of passenger flow distribution for urban rail transit based on multi-factor model

The lack of the historical data of new rail line makes the passenger flow distribution prediction be a challenge. Traditional methods always use simple factors, which can not reflect the complexity of OD distribution. This paper proposes a novel passenger flow distribution prediction method based on multi-factor model. This method obtains quantitative impact factors of OD distribution by analyzing the historical data of existing stations, and then constructs the multi-factor model. The model considers the influence of the nature of the station, as well as the impact of rail network structure, which makes it more precision. Validation experiment results show that the model is reasonable.