小汽车依赖性的综合测度及其影响因素研究  

Research on the comprehensive measurement of car dependence and its influencing factors

作　　者：何明卫[1] 邓培瑶 李健波 雷家友 刘杰 HE Mingwei;DENG Peiyao;LI Jianbo;LEI Jiayou;LIU Jie(Faculty of Transportation Engineering,Kunming University of Science and Technology,Kunming 650500,China)

机构地区：[1]昆明理工大学交通工程学院,昆明650500

出　　处：《北京交通大学学报》2025年第1期128-135,共8页JOURNAL OF BEIJING JIAOTONG UNIVERSITY

基　　金：国家自然科学基金(72361015)。

摘　　要：针对现有的小汽车依赖性测度方法考虑维度单一、影响机理不够明晰等问题,以昆明市为研究对象,基于小汽车用户出行调查数据开展小汽车依赖性综合测度及影响因素研究.考虑客观依赖、主观依赖和小汽车使用条件3个维度,运用二阶结构方程模型对小汽车依赖性进行综合测度,分析小汽车依赖性的群体差异性,并使用梯度提升决策树(Gradient Boosting Decision Tree,GBDT)模型和Shapley Additive exPlanations(SHAP)模型探究社会经济属性与建成环境对小汽车依赖性的影响机理.研究结果表明:客观依赖、主观依赖和小汽车使用条件的载荷系数分别为0.725、0.242、0.852,小汽车依赖性受到小汽车使用条件的制约,小汽车用户的客观依赖性强于主观依赖性,且不同群体对小汽车不同维度的依赖存在差异;客观建成环境对小汽车依赖性的影响(62.48%)大于社会经济属性(29.87%),感知建成环境(7.46%)对小汽车依赖性的影响较小;建成环境对小汽车依赖性的影响具有非线性关系和阈值效应.研究成果可为小汽车依赖性的测度提供一种新的思路,并为采取针对性策略降低小汽车依赖性的研究提供参考.To address the issues of existing methods for measuring car dependence,including their single-dimensional focus and lack of clarity regarding influencing mechanisms,this study conducts a comprehensive analysis of car dependence and its influencing factors,using travel survey data collected from car users in Kunming.Incorporating three dimensions,which are objective dependence,subjective dependence,and car usage conditions,the study employs a second-order structural equation model to comprehensively measure car dependence and analyze group-level differences.Subsequently,the Gradient Boosting Decision Tree(GBDT)model and the Shapley Additive exPlanations(SHAP)model are applied to explore the influence mechanisms of socio-economic attributes and built environment on car dependence.The results indicate that the loading coefficients for objective dependence,subjective dependence,and car usage conditions are 0.725,0.242,and 0.852,respectively.Car dependence is constrained by car usage conditions,with objective dependence proving stronger than subjective factors,and varying significantly across demographic groups.The objective built environment accounts for 62.48%of the variance in car dependence,higher than 29.87%for socio-economic attributes and just 7.46%for the perceived built environment with a relatively low influence.The influence of the built environment on car dependence also exhibits nonlinear relationships and threshold effects.These findings present a novel framework for measuring car dependence and provide valuable insights for developing targeted strategies to reduce car dependence.

关 键 词：交通运输规划与管理 小汽车依赖性 测度方法 GBDT 建成环境 

分 类 号：U491[交通运输工程—交通运输规划与管理]