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轨道交通车站出入口客流预测——以北京市为例

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针对轨道交通车站出入口客流精准预测问题,综合考虑车站周边土地利用情况、交通接驳条件、车站属性和吸引力等因素,构建了双层客流预测模型,包括基于多元非线性回归的交通小区层客流预测以及基于CRITIC法的出入口层客流预测。模型以可获取数据为基础,先预测交通小区内所有出入口客流总量,再将客流总量分配至交通小区的各出入口。随机选取不同类型轨道交通车站对模型有效性进行验证,结果表明,出入口日进站量的模型预测值与实际值误差在30%以内,平均误差为20%,具有较高的预测精度。
Passenger flow prediction at entrance and exit of rail transit stations:a case study of Beijing
Regarding the accurate prediction of passenger flow at the entrance and exit of rail transit stations,Considering the land use around the station,Rail transit connection conditions,station attributes and attraction,a two-level passenger flow prediction model is constructed in this paper,station attributes and attraction,a two-level passenger flow prediction model is constructed in this paper,including the passenger flow prediction at the traffic district level based on multiple nonlinear regression and the passenger flow prediction at the entrance and exit level based on the CRITIC method.On the basis of the available data,the total passenger flow of all entrances and exits in the traffic district is predicted,and then be allocated to each entrance and exit.Different types of rail transit stations are randomly selected to verify the effectiveness of the model.The results show that the error between the predicted value of the model and the actual value of the daily entry volume is within 30%,and the average error is 20%,which has a high prediction accuracy.

rail transittwo-level passenger flow prediction modelnonlinear regressionCRITIC method

马洁、刘智丽、王书灵、董皓

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北京交通大学交通运输学院,北京 100044

北京交通发展研究院,北京 100073

北京公交有轨电车有限公司,北京 100080

轨道交通 双层客流预测模型 非线性回归 CRITIC法

2024

吉林大学学报(工学版)
吉林大学

吉林大学学报(工学版)

CSTPCD北大核心
影响因子:0.792
ISSN:1671-5497
年,卷(期):2024.54(8)