交通运输系统工程与信息

交通运输系统工程与信息 ›› 2026, Vol. 26 ›› Issue (3): 134-143.DOI: 10.16097/j.cnki.1009-6744.2026.03.013

• 综合交通运输体系 • 上一篇    下一篇

地铁站点类型视角下建成环境对共享单车接驳比例的影响

陈越1a,2 ，贾顺平1a ，季千喜1a ，代斯薇1a ，许奇*1a,1b   

  1. 1. 北京交通大学，a.交通运输学院，b.综合交通运输大数据应用技术交通运输行业重点实验室，北京100044； 2. 利兹大学，交通研究所，利兹LS29JT，英国
  • 收稿日期:2026-03-17 修回日期:2026-04-20 接受日期:2026-05-06 出版日期:2026-06-25 发布日期:2026-06-23
  • 作者简介:陈越（1997—），男，湖北荆门人，博士生。
  • 基金资助:
    国家自然科学基金(72471024)。

Effects of Built Environment on Bike-Sharing Feeder Ratio Considering Metro Station Types

CHEN Yue1a,2, JIA Shunping1a, JI Qianxi1a, DAI Siwei1a, XU Qi*1a,1b   

  1. 1a. School of Traffic and Transportation, 1b. Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, China; 2. Institute for Transport Studies, University of Leeds, Leeds LS2 9JT, UK
  • Received:2026-03-17 Revised:2026-04-20 Accepted:2026-05-06 Online:2026-06-25 Published:2026-06-23
  • Supported by:
    National Natural Science Foundation of China (72471024)。

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摘要： 在“轨道-慢行”融合的背景下，本文利用2025年同一周内的地铁刷卡数据和共享单车订单数据，准确识别共享单车接驳出行，提出地铁站点共享单车吸引范围识别方法，测算不同时段、不同接驳模式下的共享单车接驳比例，结合模糊C均值聚类方法（FuzzyC-Means,FCM）和多尺度地理加权回归(Multiscale Geographically Weighted Regression, MGWR）模型，研究建成环境对不同类型地铁站点共享单车接驳比例的时空异质性影响。针对北京的案例研究表明：共享单车扩大了地铁站点传统的步行吸引半径，平均达到1.6 km。高峰时段的共享单车接驳比例均值约16%，低客流型站点略高于其他站点。MGWR结果显示高职住密度抑制接驳比例，而高混合度促进接驳比例。共享单车车辆的充足供给是保障接驳比例的关键基础。公交站点密度结果呈现地面公交与共享单车竞争与协同并存的空间分化现象，即在中心城区合作，外围地区竞争。此外，建成环境对接驳比例的影响还受到站点功能属性的调节，结果发现，居住导向型站点受地面公交竞争影响较大，就业导向型站点受交通区位影响较大。

关键词: 城市交通, 接驳方式, 地理加权回归, 共享单车, 建成环境

Abstract: Under the background of the integration of metro and active mobility, this study uses the data of 2025 Beijing metro smart-card transactions and dockless bike-sharing trip in one week to identify bike-metro feeder trips. Then it develops a method to delineate the bike-sharing catchment areas around metro stations. This paper quantifies the bike-sharing feeder ratio across time periods and feeder modes. And then it integrates the Fuzzy C-Means (FCM) clustering with Multiscale Geographically Weighted Regression (MGWR) to investigate the spatiotemporal heterogeneous effects of built environment on transfer shares for different station types. The case study of Beijing shows that bike sharing expands the traditional walking catchment radius of metro stations, reaching an average distance of approximately 1.6 km. During peak hours, the average bike-sharing feeder ratio is about 16%, with low-ridership stations showing a slightly higher proportion than other station types. The MGWR results indicate that high job housing density suppresses the bike-sharing feeder ratio, whereas a high level of land-use mix promotes it. Sufficient bike-sharing supply is a key prerequisite for maintaining a high feeder ratio. The results for bus stop density reveal spatial differentiation in the relationship between bus and bike sharing, showing both competition and complementarity: the two modes tend to be complementary in central urban areas but competitive in peripheral areas. In addition, the bike-sharing feeder ratio is not only affected by the built environment but also moderated by station functional attributes. Specifically, residential-oriented stations are more strongly affected by competition from bus, whereas employment-oriented stations are more sensitive to transport location factors.

Key words: urban transportation, feeder mode, geographically weighted regression, bike-sharing, built environment

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