基于多层模型的城市建成环境对通勤行为的影响

交通运输系统工程与信息 ›› 2018, Vol. 18 ›› Issue (2): 122-127.

基于多层模型的城市建成环境对通勤行为的影响

尹超英^1a，邵春福^*1b，王聘玺²，米雪玉^1a

1. 北京交通大学 a. 城市交通复杂系统理论与技术教育部重点实验室，b. 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；2. 北京交通发展研究院，北京 100073

收稿日期:2017-10-23 修回日期:2018-02-01 出版日期:2018-04-25 发布日期:2018-04-25
作者简介:尹超英(1989-)，女，山西忻州人，博士生.
基金资助:
国家自然科学基金/National Natural Science Foundation of China(51338008)；中央高校基本科研业务费专项资金/ The Fundamental Research Funds for the Central Universities(2017YJS087).

Impacts of Built Environment on Commuting Behavior Based on a Multilevel Modeling Approach

YIN Chao-ying^1a, SHAO Chun-fu^1b, WANG Pin-xi², MI Xue-yu^1a

1a. MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, 1b. Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, China; 2. Beijing Transport Institute, Beijing 100073, China

Received:2017-10-23 Revised:2018-02-01 Online:2018-04-25 Published:2018-04-25

摘要/Abstract

摘要：

为研究城市建成环境对居民通勤行为的影响，考虑个体社会经济属性和交通小区建成环境属性的跨层次结构，建立多层模型，分别分析了个体社会经济属性层面和交通小区建成环境层面对通勤时间及通勤距离的影响，并利用长春市居民出行调查数据标定模型参数. 结果表明：多层模型比传统的回归模型拟合效果更好；控制个体社会经济属性特征后，土地利用混合度、交叉口密度及公共交通站点密度对居民通勤出行时间和距离的影响均呈现显著的负效应，而居民居住地到城市中心商务区(CBD)的距离仅对通勤距离有显著的正向影响.研究结果可为通过城市规划优化通勤结构提供理论支持.

关键词: 交通工程, 建成环境, 通勤时间, 通勤距离, 多层模型

Abstract:

Considering the hierarchical characteristics of social-demographic factors at individual level and built environment factors at traffic analysis zone (TAZ) level, a multilevel approach is proposed to investigate the influences of built environment on commuting time and distance. The impacts of social- demographic factors at individual level and built environment factors at TAZ level on commuting time and distance are analyzed respectively. And the model parameters are estimated based on Changchun household travel survey data. The study infers that the multilevel modeling approach yields better fitting results than the traditional regression model. Additionally, after controlling for commuters’ social-demographics characteristics, the model results show that land use mix, intersection density and transit station density have significantly negative influences on commuting time and distance. And the distance to Central Business District (CBD) is positively associated with commuting distance merely. The research results can provide theory basis for optimizing the commuting structure by means of urban planning.

Key words: traffic engineering, built environment, commuting time, commuting distance, multilevel model

中图分类号:

U491

尹超英，邵春福，王聘玺，米雪玉. 基于多层模型的城市建成环境对通勤行为的影响[J]. 交通运输系统工程与信息, 2018, 18(2): 122-127.

YIN Chao-ying, SHAO Chun-fu, WANG Pin-xi, MI Xue-yu. Impacts of Built Environment on Commuting Behavior Based on a Multilevel Modeling Approach[J]. Journal of Transportation Systems Engineering and Information Technology, 2018, 18(2): 122-127.

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