您当前的位置：
首页 >
文章列表页 >
Analysis of influence of built environment of spatial units of different housing types on commuting mode choice
更新时间：2025-05-26

    • Analysis of influence of built environment of spatial units of different housing types on commuting mode choice

    • “The latest research reveals that the hybrid Logit model can more accurately predict residents' commuting mode choices, providing new ideas for improving the built environment and guiding green travel.”
    • Journal of Jilin University(Engineering and Technology Edition)   Vol. 55, Issue 2, Pages: 554-565(2025)
    • 作者机构：

      1.同济大学 道路与交通工程教育部重点实验室， 上海 201804

      2.同济大学 城市交通研究院， 上海 201804

    • DOI：10.13229/j.cnki.jdxbgxb.20230387    

      CLC： U491

    • Received：19 April 2023，

      Published：01 February 2025

    移动端阅览

  • WU Jiao-rong,LIU Xu-dong.Analysis of influence of built environment of spatial units of different housing types on commuting mode choice[J].Journal of Jilin University(Engineering and Technology Edition),2025,55(02):554-565. DOI： 10.13229/j.cnki.jdxbgxb.20230387.

  •  
  •  

0

Views

5

下载量

0

CSCD

Alert me when the article has been cited
提交
Tools
Download
Export Citation
Share
Add to favorites
Add to my album

Related Articles

Influence of built environment on commuting mode choice considering spatial heterogeneity
Multi-scale spatial heterogeneity analysis of influencing factors of ride-hailing travel demand
Impacts of built environment on commuting mode choice considering spatial autocorrelation
Residents' commuting time model under the nonlinear impact of urban built environment
Influence of urban built environment on car commuting considering parking availability

Related Author

YIN Chao-ying
SHAO Chun-fu
WANG Xiao-quan
XIONG Zhi-hua
PAN Yi-yong
XU Jia-cong
YOU Yi-wen
QUAN Yong-jun

Related Institution

Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University
College of Automobile and Traffic Engineering， Nanjing Forestry University
Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport， Beijing Jiaotong University
School of Traffic and Transportation， Lanzhou Jiaotong University
Business School， University of Shanghai for Science and Technology
0