Metro Station Classification Based on Boarding and Alighting Passenger Flows and Ridership Impact Factors

被引：0
|
作者：
Pang L. [1 ]
Ren L.-J. [1 ]
Zhang Z.-H. [2 ]
Yun Y.-X. [1 ]
机构：
[1] School of Architecture, Tianjin University, Tianjin
[2] School of Architecture, Yantai University, Shandong, Yantai
来源：
Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology | 2023年 / 23卷 / 04期
基金：
中国国家自然科学基金;
关键词：
metro ridership; multiscale geographically weighted regression; ridership impact factors; station type; urban traffic;
D O I：
10.16097/j.cnki.1009-6744.2023.04.019
中图分类号：
学科分类号：
摘要：
Existing studies have deep analysis on the metro ridership characteristics and its the impact factors, however, the impact factors of passenger flow for different types of metro stations can be further investigated. This paper utilized a time series clustering method which introduced boarding and alighting passenger flow characteristics to classify metro stations in Tianjin city of China, and developed an index system of effect factors according to the built environment, socio-economic, station attributes, and complex network characteristics based on multi-source geographic big data. Three regression models, Ordinary least squares, Geographically Weighted Regression and Multi-Scale Geographically Weighted Regression were used to analyze the factors that affect the ridership and the degree of impactfor different types of stations. The case study in Tianjin indicated that: (1) there are three main categories of stations based on the time-varying characteristics of passenger flow, residential-oriented, employment-oriented and commercial-residential balance stations. The spatial distribution and surrounding land use characteristics of each station were significantly different. (2) For the ridership impact factors at the residential-oriented stations, the MGWR model showed best fitting results. However, for employment-oriented and commercial-residential balance stations, the OLS model demonstrated better fitting results but the differences were marginal compared to other models. (3) The ridership impact factors for different types of stations were significantly different, and the differences were also shown in the direction and intensity of the impact factors. (4) The influence of bus station density and opening hours on the ridership of residential-oriented stations had significant spatial heterogeneity. The study results provided a planning guidance onstation classification and zoning and further improvement of the effectiveness of rail transit operation and development of TOD at rail transit stations in Tianjin. © 2023 Science Press. All rights reserved.
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页码：184 / 193
页数：9
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