摘要
基于社区建成环境的5D维度选取了人口密度、土地利用多样性、公交服务水平等6个指标刻画社区建成环境,以《社区生活圈规划技术指南》中15 min社区生活圈与步行速度为依据,形成社区生活圈测度范围,结合POI(point of interest)数据、道路网络等地理空间数据测度建成环境。以保定市居民出行行为调查数据作为实证研究数据,构建了考虑非线性效应的梯度提升决策树(gradient boosting decision tree,GBDT)模型。结果表明:在模型拟合度方面,GBDT模型比线性假设的OLS(ordinary least squares)模型调整后R 2(可决系数)提高了76%;在社区建成环境指标贡献度方面,土地利用混合度(19.10%)与距离市中心的距离(17.23%)对中等收入人群VMT的贡献度最大,说明合理的土地利用规划对调节中等收入人群小汽车使用行为的重要作用;在建成环境指标的非线性关系方面,建成环境因子与VMT均具有非线性关系,其中土地利用混合度、公交站点密度与距离市中心的距离对VMT的影响与驾龄存在一定的交互效应,通过部分相关图的拐点分析得到社区建成环境规划的定量依据是未来低碳社区建设的基础。
With an increasing proportion of middle-income groups in the population structure,quantitative analysis of the nonlinear impact of community built environment on vehicle miles traveled(VMT)of middle-income groups has become an important basis for finely guiding the community life circle to create a green travel built environment.Based on the 5D of the built environment,this paper selects six indicators such as population density,land use diversity and public transport service levels to describe the built environment of a community.Based on the 15-minute community life circle and walking speed in Technical Guide for Community Life Circle Planning,the measurement range of the community life circle is formed.The built environment is measured by combining point of interest(POI)data,road networks and other geospatial data.Taking Baoding residents’travel behavior survey data as the source of empirical research,this paper constructs a gradient boosting decision tree(GBDT)model that considers nonlinear effects.In terms of model fitting,the GBDT model improves the adjusted R 276%higher than the ordinary least squares(OLS)model with linear assumptions does,and performs better than machine learning models such as Support Vector Machine(SVM)and Random Forest(RF)do,indicating that the GBDT model has better adaptability in this study.In terms of the contribution of built environment indicators,the built environment attributes have a greater effect on VMT than individual social and economic attributes do,with land use mixing degree(19.10%)and distance from the city center(17.23%)contributing the most to VMT of middle-income people,which reflects the important role of reasonable land use planning in regulating middle-income people’s car use.In addition,the lowest contributor is public transportation service level(5.72%).This may be due to the fact that the middle-income group has a high travel demand with high time efficiency and high quality requirements for travel modes,and based on the preliminary research,the existing pu
作者
王振科
白云鹏
WANG Zhenke;BAI Yunpeng(College of Traffic and Transportation,Chongqing Jiaotong University,Chongqing 400074,China;Chongqing Hengchang Planning and Design Institute,Chongqing 400074,China;Chongqing Municipal Research Institute of Design,Chongqing 400014,China)
出处
《重庆理工大学学报（自然科学）》
CAS
北大核心
2023年第5期159-168,共10页
Journal of Chongqing University of Technology：Natural Science
基金
重庆市教育委员会科学技术研究计划项目(KJQN202001611)
重庆市教育委员会“成渝地区双城经济圈建设”科技创新项目(KJCXZD2020029)。
关键词
城市交通
建成环境
机动车行驶里程
GBDT模型
非线性效应
urban traffic
built environment
vehicle miles traveled
gradient boosting decision tree model
non-linear effect
