交通运输系统工程与信息

交通运输系统工程与信息 ›› 2022, Vol. 22 ›› Issue (4): 194-201.DOI: 10.16097/j.cnki.1009-6744.2022.04.022

• 系统工程理论与方法 • 上一篇    下一篇

考虑群体异质性的建成环境与老年人慢行出行关系研究

吴静娴，钱依楠，韩印*   

  1. 上海理工大学，管理学院，上海 200093
  • 收稿日期:2022-04-30 修回日期:2022-05-25 接受日期:2022-06-20 出版日期:2022-08-25 发布日期:2022-08-23
  • 作者简介:吴静娴(1987- )，女，江苏盐城人，讲师，博士。
  • 基金资助:
    国家自然科学基金；中国地震局工程力学研究所基本科研 业务费专项资金

Relationship Between Built Environment and Elderly Active Travel of Based on Group Heterogeneity

WU Jing-xian, QIAN Yi-nan, HAN Yin*   

  1. Business School, University of Shanghai for Science and Technology, Shanghai 200093, China
  • Received:2022-04-30 Revised:2022-05-25 Accepted:2022-06-20 Online:2022-08-25 Published:2022-08-23
  • Supported by:
    National Natural Science Foundation of China(71971140)；Scientific Research Fund of Engineering Mechanics, China Earthquake Administration(2020D23)。

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摘要： 健康老龄化背景下，慢行出行是提升老年人身心健康、生活品质的重要方式，而建成环境是影响老年人慢行出行的重要因素。本文以2013年南京市老年人出行实测数据为基础，利用潜在类别聚类方法对老年群体进行异质性分析，分类建立随机森林模型研究建成环境指标对不同老年群体慢行出行时间的重要度影响及两者之间的非线性关联。研究结果表明：以性别、是否退休、学历、家庭收入以及学龄前儿童这5个类别变量作为外显变量，可将老年群体划分成两类，各自建立的老年人慢行时间模型整体拟合优度较好；其中，影响第1类老年群体的关键建成环境变量有慢行路网密度、交叉口数和地铁站邻近度，第2类老年群体慢行出行时间的影响因素主要有地铁站邻近度、慢行路网密度和住宅密度，另外同一建成环境指标对两类老年群体慢行出行时间的非线性关联也不相同。研究结果可为制定差异化的老年宜居环境优化政策，提升老年人生活品质以及实现健康老龄化提供理论依据。

关键词: 城市交通, 建成环境, 随机森林, 老年群体异质性, 非线性影响, 慢行出行

Abstract: In the context of healthy aging, active travel is an effective way to improve the physical and mental health and quality of life of the elderly. The built environment is an important factor affecting the active travel of the elderly. Using data from 2013 Nanjing Household Travel Survey and built environment data, this study analyzed the heterogeneity of elderly groups based on latent class clustering, and then used a random forest method to scrutinize the importance magnitude of built environment indicators on the active travel time of different elderly groups and the nonlinear relationship between the build environment and elderly active travel. The results show that the five category variables of gender, whether retired, education, household income, and whether has preschool children in the family can be used as the exogenous variables to further classify the elderly groups into two main categories. The overall goodness of fit of the classified random forest model were significantly improved. The major built environment variables that significantly affect the first identified elderly group are the density of the active road network, the number of intersections, and the proximity to subway stations. The factors that significantly affect the active travel time of the second identified elderly group are the proximity to subway stations, the density of the active road network, and the density of residential buildings. The non-linear relationships of the same built environment indicator to the active travel time of the two elderly groups are different. The result of this study provides a theoretical reference for the policy making to facilitate the elderly travel environment and ultimately advance the healthy aging.

Key words: urban traffic, built environment, random forest, heterogeneity of the elderly population, nonlinear effects, active travel

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