广东工业大学学报 ›› 2021, Vol. 38 ›› Issue (01): 32-38.doi: 10.12052/gdutxb.200141

• 综合研究 • 上一篇    下一篇

新冠肺炎疫情不同阶段居民出行方式选择行为建模分析

胡三根, 王润鸿, 王小霞, 刘圆圆   

  1. 广东工业大学 土木与交通工程学院，广东 广州 510006
  • 收稿日期:2020-10-29 出版日期:2021-01-25 发布日期:2020-12-01
  • 通信作者: 王小霞(1981-)，女，讲师，博士，主要研究方向为交通运输规划、交通行为，E-mail：xiaoxiawang2006@163.com E-mail:xiaoxiawang2006@163.com
  • 作者简介:胡三根(1989-)，男，讲师，博士，主要研究方向为交通系统建模与仿真
  • 基金资助:
    国家自然科学基金资助项目(61803092)；广东工业大学青年基金重点项目(18QNZD003)；广东工业大学博士启动基金项目(18ZK0046)

Modeling of Travel Mode Choice Behavior of Residents in Different Stages of the COVID-19 Epidemic

Hu San-gen, Wang Run-hong, Wang Xiao-xia, Liu Yuan-yuan   

  1. School of Civil and Transportation Engineering, Guangdong University of Technology, Guangzhou 510006, China
  • Received:2020-10-29 Online:2021-01-25 Published:2020-12-01

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摘要： 针对新冠肺炎疫情初期、中期及后期3个不同阶段, 从出行者属性与出行特性两个方面分析居民出行方式选择行为的影响因素。由于出行方式之间存在相互关联作用, 故采用Nested Logit模型方法建立出行方式选择行为决策模型。利用中山市坦洲镇居民出行意向调查数据(Stated Preference, SP), 分别分析新冠肺炎疫情各个阶段影响居民出行方式选择行为的影响因素。研究结果表明: 不同疫情时期, 影响居民出行方式选择的显著性因素发生了明显变化, 而且同一因素在不同疫情时期下的影响程度也存在差异。这些结果可以为有关部门在面对突发公共卫生事件时, 制定非常态的交通管理措施提供支持。

关键词: 居民出行方式, Nested Logit模型, 影响因素, 新冠肺炎疫情

Abstract: Considering the impact of novel coronavirus pneumonia (COVID-19), the main factors influencing travel mode choice behavior of residents were analyzed from the aspects of traveler attributes and travel characteristics for the three periods of COVID-19 epidemic: early-stage, mid-stage, and late-stage. The Nested Logit model was adopted to establish the travel mode choice model because of a correlation between travel modes. Influence factors of travel mode choice behavior in different stages of COVID-19 epidemic were analyzed using the SP data of residents in Tanzhou Town, Zhongshan City. The results showed that the significant factors influencing travel mode choice behavior were different in different epidemic periods, and the influence degree of the same factor was also different in different epidemic periods. These results can provide support for relevant authorities to formulate abnormal traffic management measures under public health emergencies.

Key words: travel mode choice, Nested Logit model, influential factors, COVID-19 epidemic

中图分类号: 

  • U491
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