吉林大学学报(工学版) ›› 2025, Vol. 55 ›› Issue (7): 2233-2242.doi: 10.13229/j.cnki.jdxbgxb.20231050

• 交通运输工程·土木工程 • 上一篇    

建成环境对共享单车时间集聚模式的非线性影响

戢晓峰(),邓若凡,乔新,关昊天   

  1. 昆明理工大学 交通工程学院,昆明 650500
  • 收稿日期:2023-10-05 出版日期:2025-07-01 发布日期:2025-09-12
  • 作者简介:戢晓峰(1982-),男,教授,博士.研究方向:交通大数据.E-mail: yiluxinshi@sina.com
  • 基金资助:
    云南省交通运输厅科技创新及示范项目(2022-27(二))

Nonlinear influence of built environment on temporal aggregation modes of shared bicycles

Xiao-feng JI(),Ruo-fan DENG,Xin QIAO,Hao-tian GUAN   

  1. College of Transportation Engineering,Kunming University of Science and Technology,Kunming 650500,China
  • Received:2023-10-05 Online:2025-07-01 Published:2025-09-12

摘要:

针对共享单车潮汐式供需失衡问题,从社会人口、交通设计与土地利用3个维度构建了建成环境指标体系,构建基于凝聚层次聚类模型提炼共享单车典型时间集聚模式,使用随机森林与沙普利加法解释模型揭示两者之间的非线性关系与阈值效应,并以云南省昆明市为例进行验证。结果表明:共享单车时间集聚模式主要为先入后出模式与先出后入模式。建成环境与共享单车时间集聚模式间存在显著的非线性关系,共享单车时间集聚模式主要受公交线网密度、公园景点邻近度、地铁站点邻近度和公司企业POI密度影响。地铁站点邻近度<0.5 km时,对共享单车时间集聚表现为先入后出模式概率具有抬升作用;公司企业密度<25个/栅格时,对其具有压降作用。

关键词: 交通运输系统工程, 共享单车, 时间集聚模式, 随机森林分类器, 非线性影响, 建成环境

Abstract:

Aiming at the problem of tidal supply-demand imbalance of shared bicycles, a built environment indicator system was constructed from the three dimensions of socio-demographic, transportation design, and land use. Based on the Agglomerative Hierarchical Clustering model, typical time-aggregation patterns of shared bicycles were obtained from clustering. The nonlinear relationship and the threshold effect between them were revealed by using the Random Forest and SHapley Additive exPlanations models. Ultimately, Kunming was an example to prove that. The results show that the temporal aggregation modes of shared bicycles mainly show the first-in-last-out mode and the first-out-last-in mode, accounting for 91.4% of the sum of all modes. There is a significant nonlinear relationship between the built environment and the temporal aggregation modes of shared bicycles. The temporal aggregation modes of shared bicycles are primarily influenced by the density of the bus line network, proximity of parks and attractions, proximity of metro stations, and POI density of companies. When the proximity of metro stations is less than 0.5 km, there is an elevating effect on the probability of showing the first-in-last-out mode. When the POI density of companies is less than 25 per cell, there is a depressing effect on the probability of showing the first-in-last-out mode.

Key words: engineering of communication and transportation system, shared bicycle, temporal aggregation modes, random forest classifier, nonlinear influence, built environment

中图分类号: 

  • U491.225

表1

建成环境指标信息"

维度指标名称指标释义单位

社会

人口

居住密度栅格内居住POI数量个/栅格

交通

设计

公交站点密度栅格内公交站点数量个/栅格
交叉口密度栅格内交叉口数量个/栅格
路网密度栅格内道路总长度m/栅格
公交线网密度栅格内公交线路总长度km/栅格
地铁站点邻近度栅格中心到最近地铁站的直线距离km
公交站点邻近度栅格中心到最近公交站的直线距离m

土地

利用

体育休闲POI密度栅格内体育休闲POI数量个/栅格
公司企业POI密度栅格内公司企业POI数量个/栅格
公园景点POI密度栅格内公园景点POI数量个/栅格
购物服务POI密度栅格内购物服务POI数量个/栅格
餐饮服务POI密度栅格内餐饮服务POI数量个/栅格
商圈邻近度栅格中心到最近商场或超级市场距离m
公园景点邻近度栅格中心到最近公园景点距离m
土地利用混合度栅格内5类POI的熵指数

图1

研究区域示意图"

表2

自变量描述性统计"

自变量VIF均值标准差
交叉口密度/(个·栅格-12.254.244.72
公交站点密度/(个·栅格-11.191.801.66
体育休闲POI密度/(个·栅格-12.216.628.95
公司企业POI密度/(个·栅格-11.5528.0930.62
公园景点POI密度/(个·栅格-11.160.952.76
居住密度/(个·栅格-12.456.986.29
购物服务POI密度/(个·栅格-12.28111.14150.64
餐饮服务POI密度/(个·栅格-12.5556.6952.70
公交站点邻近度/m2.60201.81199.92
公园景点邻近度/m2.71393.68436.48
公交线网密度/(km·栅格-11.324.203.52
路网密度/(km·栅格-11.491 661.041 155.09
商圈邻近度/m1.12189.53125.54
地铁站点邻近度/km1.220.850.57
土地利用混合度1.960.640.12

图2

凝聚层次聚类树形图"

图3

时间序列曲线聚类结果"

图4

分类器P-R曲线图"

图5

自变量重要度排序"

图6

自变量正负向影响"

图7

关键因素部分依赖图"

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