考虑空间自相关的建成环境对通勤方式选择的影响  

Impacts of built environment on commuting mode choice considering spatial autocorrelation

作　　者：尹超英 陆颖 邵春福[2] 马健霄[1] 许得杰[3] YIN Chao-ying;LU Ying;SHAO Chun-fu;MA Jian-xiao;XU De-jie(College of Automobile and Traffic Engineering,Nanjing Forestry University,Nanjing 210037,China;Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport,Beijing Jiaotong University,Beijing 100044,China;School of Traffic and Transportation,Lanzhou Jiaotong University,Lanzhou 730070,China)

机构地区：[1]南京林业大学汽车与交通工程学院,南京210037 [2]北京交通大学,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 [3]兰州交通大学交通运输学院,兰州730070

出　　处：《吉林大学学报（工学版）》2023年第7期1994-2000,共7页Journal of Jilin University:Engineering and Technology Edition

基　　金：国家自然科学基金项目(72204114,52072025);教育部人文社会科学研究基金项目(22YJC630191);江苏省高校社科基金项目(2021SJA0147).

摘　　要：为探究城市空间结构对居民通勤行为的影响,考虑居民通勤出行行为在相邻交通小区间具有相似性这一特性,建立能够捕捉通勤行为空间自相关的层次Bayesian模型,分析交通小区尺度建成环境影响下居民个体通勤方式选择行为决策过程。研究结果表明:居民通勤方式选择行为在交通小区间的空间自相关是显著存在的;采用质点空间距离矩阵的模型拟合效果最优;除个体尺度社会经济特征外,交通小区尺度建成环境特征依然是影响居民通勤方式选择的重要因素;其中,土地利用混合度、公共交通站点密度及交叉口密度均与居民小汽车通勤方式选择有显著的负相关关系,表明通过适当增加居民居住交通小区内的公共交通站点数量、提高交通小区土地利用混合度和优化街区路网设计可有效降低居民使用小汽车通勤的概率。Considering the similarity in residents′commuting behavior living in nearby zones,several multilevel Bayesian models are employed to examine the impacts of built environment at traffic analysis zone(TAZ)levels on commuting mode choice.Bayesian models can capture the spatial autocorrelation of commuting behavior by incorporating adjacency matrixes to represent the spatial relationships between TAZs.The results show that the spatial autocorrelation significantly exists in residents′commuting behavior.In addition,the model incorporating a centroid distance adjacent matrix has the best performance among the compared models.After controlling for socioeconomic characteristics at the individual levels,built environment characteristics are important factors of car commuting.Specifically,land use mix,public transit station density and intersection density have negative impacts on commuting by car.These results suggest that increasing the number of public transit stations,promoting more balanced land use and optimizing road network designs are important for car commuting reductions.The findings suggest that the optimization of built environment is important for encouraging low-carbon travel.

关 键 词：交通工程 建成环境 通勤方式选择 空间自相关 层次Bayesian模型 

分 类 号：U491[交通运输工程—交通运输规划与管理]