交通运输系统工程与信息

交通运输系统工程与信息 ›› 2016, Vol. 16 ›› Issue (1): 176-181.

• 系统工程理论与方法 • 上一篇    下一篇

基于态度—行为模型的低收入通勤者出行方式选择

程龙1,2，陈学武*1, 2，杨硕1, 2   

  1. 1. 东南大学江苏省城市智能交通重点实验室，南京210096；2. 现代城市交通技术江苏高校协同创新中心，南京210096
  • 收稿日期:2015-07-27 修回日期:2015-09-28 出版日期:2016-02-25 发布日期:2016-02-25
  • 作者简介:程龙（1989-），男，安徽淮北人，博士生.
  • 基金资助:

    国家自然科学基金项目/National Natural Science Foundation of China（51178109）；国家重点基础研究发展计划项 目/State Key Development Program of Basic Research of China（2012CB725402.

Low-income Commuters’Mode Choice Utilizing Attitude-behavior Model

CHENG Long1, 2, CHEN Xue-wu1, 2, YANG Shuo1, 2   

  1. 1. Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 210096, China; 2. Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Nanjing 210096, China
  • Received:2015-07-27 Revised:2015-09-28 Online:2016-02-25 Published:2016-02-25

PDF

摘要：

为了分析城市低收入通勤者交通方式选择行为，揭示个体社会经济属性、活动 属性和潜在态度变量对出行者出行方式选择的影响，基于抚顺市居民一日出行调查数 据，采用态度—行为模型探究低收入通勤者出行方式选择机理.首先基于多指标多原因模 型分析影响态度变量的外在因素，结果表明性别、驾照拥有情况和年龄对态度变量的构 成影响较大.然后，分别建立含潜变量和不含潜变量的多项Logit 模型，发现含潜变量的选 择模型更能解释出行行为，社会经济属性、活动属性和态度变量对低收入通勤者出行方 式选择影响存在一定差异.

关键词: 交通工程, 出行方式选择, 态度&mdash, 行为, 低收入通勤者, 多指标多原因模型, 多项Logit模型

Abstract:

To analyze modal choice behavior of low income commuters and reveal the influence of individual’s socio-demographics, activity attributes and latent attitude variables on mode choice, an integrated attitude-behavior model is utilized to estimate these relationships based on Fushun activity-based travel survey. Firstly, based on a multiple indicators multiple causes model to analyze effects of explanatory factors on attitude variables, results indicate gender, age and driving license possession play important roles on attitude formation. Then, multinomial Logit models with and without latent variables are both estimated. Findings show that the latent variables enriched choice model provides additional explanation on travel behavior. Socio-demographics, activity attributes and attitude variables exert different impacts on low income commuters’mode choice.

Key words: traffic engineering, mode choice, attitude-behavior, low income commuters, multiple indicators multiple causes model, multinomial Logit model

中图分类号: