A passenger volume prediction method based on temporal and spatial characteristics for urban rail transit
YUAN Jian
WANG Peng
WANG Yue
YANG Xin
Abstract：With the expanding of urban rail transit network revenue length and the increasing of its passenger volume,the passenger volume for some subway stations is susceptible to rapid chan-ges,which can easily incur uneven distribution of the entire network traffic.It could therefore in-crease the difficulty of rail transit operations and probability of operational incidents.On the basis of passenger volume data collected from practical operation,this paper analyzes the temporal and spatial characteristics of the passenger volume.It also proposes a passenger volume prediction method using the Bayesian network to predict the passenger volume of certain subway stations. Based on practical data,these numerical experiments demonstrate that the proposed method can achieve an mean absolute percentage error below 0.1 when predicting,proving the model is highly accurate.
Keywords：urban rail transitpassenger volume predictionBayesian networktemporal and spatial characteristics
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 42-48 )