Journal of South China University of Technology(Natural Science) >

2022 , Vol. 50 >Issue 7: 56 - 65

DOI: https://doi.org/10.12141/j.issn.1000-565X.210651

Traffic & Transportation Engineering

Methods of Determining the Range of Non-motorized Travel Influence Area Under the Concept of “Metro Transit Micro-center”

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  • 1.College of Metropolitan Transportation，Beijing University of Technology，Beijing 100124，China
    2.Jinan Road，Bridge and Tunnel Service Center，Jinan 250101，Shandong，China
    3.Beijing Transport Institute，Beijing 100161，China
陈廷照（1993-），女，博士生，主要从事交通出行行为、大数据挖掘研究。E-mail：ctzlzhao@163.com

Received date: 2021-10-12

  Online published: 2022-01-30

Supported by

the National Key Research and Development Program of China(2018YFB1600900)

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Abstract

In response to the concept of land-use integration and creating micro-center around metro station in Beijing, this study extracted 23 quantitative indicators from public passenger flow, road network design, population density and land diversity to quantitatively analyze the built environment and travel characteristics of the non-motorized influence area based on multi-source big data. The connection characteristics of shared bicycles were taken into particular consideration. In order to compensate for the shortcomings of determining the influence range of metro stations by the traveler’s walking time, a classification model incorporating principal component analysis and K-means clustering was proposed to define the non-motorized influence area. Taking Beijing as an example, the study divided the metro stations into 4 clusters: inefficient connection-weak connectivity-residence oriented, efficient connection-high connectivity-balanced, efficient connection-weak connectivity-mixed, and efficient connection-high connectivity-work oriented. In order to verify the rationality of the clustering, the spatial auto-correlation was used to judge the spatial dependence of indicators. The results show that the spatial distributions of clusters 1, 3 and 4 do not differ significantly from the random model, while cluster 2 efficient connection-high connectivity-balanced stations has auto-correlation characteristics in space. Finally, based on the clustering results, the non-motorized influence areas of the metro stations were delineated as 2 000, 1 600, 1 600, and 1 700 m, respectively. The clarification of the non-motorized influence range of different metro station types can help urban planners determine the scope of micro-center construction and also lay the foundation for transport-oriented development of urban in the future.

Key words： metro micro-center; influence factor; principal component analysis; K-means clustering; non-motorized travel influence area

Cite this article

CHEN Tingzhao, CHEN Yanyan, WANG Zili, et al . Methods of Determining the Range of Non-motorized Travel Influence Area Under the Concept of “Metro Transit Micro-center”[J]. Journal of South China University of Technology(Natural Science), 2022 , 50(7) : 56 -65 . DOI: 10.12141/j.issn.1000-565X.210651

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