建成环境对城市停车需求影响的非线性模型

为精细化把握城市建设项目在微观空间尺度下的停车需求规律,从空间视角探究停车需求与建成环境之间的关系.通过高峰小时建筑物单位面积的停车生成数表征停车需求,以土地利用混合度、路网密度、公交服务水平等9个因子描述建成环境,分别构建建成环境对停车需求影响的普通最小二乘(Ordinary Least Squares,OLS)模型...

Nonlinear Model of Impact of Built Environment on Urban Parking Demand

This paper investigates the relationship between parking demand and the built environment from a spatialperspective to understand the parking demand trend from the micro- spatial scale of urban construction projects. Theparking demand is represented by the number of parking generations per unit area of the building during peak hours,and the built environment is characterized by 9 factors including the degree of mixed land use, road density, and servicelevel of urban public transport. The Ordinary least- squares (OLS) model and the gradient boosting decision tree(GBDT) model are developed to describe the impact of built environment on parking demand. Based on the parkingdata of commercial parking lots in the main urban area in Baoding, China, this study conducted an empirical analysis ofthe model with the multi-source heterogeneous data including parking survey data, the Point of Interest (POI) data androad network data. The results show that the GBDT model considering the non-linear effect has a better fitting degreethan the OLS model. From the perspective of impact contribution, construction indicators and location are two builtenvironmental factors significantly affect parking demand, the contributions are respectively18.92% and 15.23%. Theintersection density has the least contribution, which is 5.19%. In terms of non-linear relationship, both builtenvironmental factors and parking demand have non- linear relationship and threshold effect. In addition to the Ushaped relationship of intersection density and population density with parking demand, the relationship of otherfactors and parking demand overall remains positive or negative correlations.