[1]安 东,蔺海娣,陈思美.基于MGWR模型的轨道站点客流时空影响因素研究——以西安地铁1—6号线为例[J].西安建筑科技大学学报(自然科学版),2023,55(01):20-26.[doi:10.15986/j.1006-7930.2023.01.003 ]
　AN Dong,LIN Haidi,CHEN Simei.Research on temporal and spatial influencing factors of passenger flow at rail stations based on MGWR model:Taking Xi'an Metro Line 1—6 as an example[J].J. Xi'an Univ. of Arch. & Tech.(Natural Science Edition),2023,55(01):20-26.[doi:10.15986/j.1006-7930.2023.01.003 ]
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基于MGWR模型的轨道站点客流时空影响因素研究——以西安地铁1—6号线为例()
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西安建筑科技大学学报（自然科学版）[ISSN:1006-7930/CN:61-1295/TU]

卷:
55
期数:
2023年01期
页码:
20-26
栏目:
出版日期:
2023-02-28

文章信息/Info

Title:
Research on temporal and spatial influencing factors of passenger flow at rail stations based on MGWR model:Taking Xi'an Metro Line 1—6 as an example
文章编号:
1006-7930(2023)01-0020-07
作者:
安 东1; 蔺海娣1; 陈思美2
(1.西安市城市规划设计研究院,陕西 西安 710082; 2.西安市交通规划设计研究院有限公司,陕西 西安 710082)
Author(s):
AN Dong1;  LIN Haidi1;  CHEN Simei2
(1.Xi'an Urban Planning and Design Institute, Xi'an 710082, China; 2.Xi'an Transportation Planning and Design Institute Co. Ltd., Xi'an 710082, China)
关键词:
城市轨道交通;  高峰客流;  时空异质性;  MGWR模型
Keywords:
Urban rail transit;  Peak passenger flow;  Spatiotemporal heterogeneity;  MGWR model
分类号:
U293.1+3
DOI:
10.15986/j.1006-7930.2023.01.003
文献标志码:
A
摘要:
为探究轨道站点客流时空分布差异及影响因素,以西安市地铁1—6号线为例,结合多源数据构建混合地理加权回归(MGWR)模型,定量分析建成环境及用地特征、交通接驳设施及站点自身属性因素对高峰时段进出站客流的影响.结果表明:西安市轨道站点客流存在显著的空间相关性,同最小二乘(OLS)模型相比,MGWR模型拟合优度更高,能够精确刻画客流与各因素的时空影响关系; 公交线路数、居住用地面积、商业用地面积是轨道站点客流的显著影响因素,受高峰时段和出行行为的影响,不同变量的回归系数存在明显差异; 各影响因素对客流的影响效果呈现不同程度的空间差异,对未来轨道交通周边规划设计提供参考.
Abstract:
In order to explore the temporal and spatial distribution differences and influencing factors of passenger flow at rail stations, this paper takes Xi'an Metro Line 1-6 as an example, constructs a mixed geographically weighted regression(MGWR)model combined with multi-source data, and quantitatively analyzes the influences of built environment, land use characteristics, transport access facilities and station attributes on passenger flow in and out of the station during peak hours. The results show that there is a significant spatial correlation in the passenger flow of Xi'an rail stations. Compared with Ordinary Least Square(OLS)model, MGWR model has higher goodness of fit, and can deeply describes the spatiotemporal influence relationship between passenger flow and various factors. Affected by peak hours and travel behavior, the regression coefficients of different variables are significantly different. The effects of various influencing factors on passenger flow show different degrees of spatial differences, which provides a reference for future planning and design of rail transit. Affected by peak hours and travel behavior, the regression coefficients of different variables vary significantly. The effect of each influencing factor on passenger flow shows different degrees of spatial disparity, which provides a reference for the planning and design of the surrounding areas of rail transit in the future.

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备注/Memo

备注/Memo:
收稿日期:2022-06-30修改稿日期:2023-01-18
基金项目:陕西省自然科学基础研究计划项目(2016JM5063)
第一作者:安 东(1986—),男,硕士,高级工程师,主要从事综合交通、轨道交通及交通环境方面的研究. E-mail: 125290635@qq.com
更新日期/Last Update: 2023-02-20