Journal of Guangdong University of Technology ›› 2021, Vol. 38 ›› Issue (01): 32-38.doi: 10.12052/gdutxb.200141

• Comprehensive Studies • Previous Articles     Next Articles

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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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

CLC Number: 

  • U491
[1] 罗强, 胡三根, 龚华炜, 等. 城市道路交通安全评价体系研究与模型构建[J]. 广西大学学报(自然科学版), 2017, 42(2): 587-592.
LUO Q, HU S G, GONG H W, et al. Model building and research of urban road traffic safety evaluation system [J]. Journal of Guangxi University (Nat Sci Ed), 2017, 42(2): 587-592.
[2] 韩志玲, 陈艳艳, 李佳贤, 等. 阻断事件影响下城际出行行为[J]. 北京工业大学学报, 2019, 45(05): 51-61.
HAN Z L, CHEN Y Y, LI J X, et al. Intercity travel behavior under the influence of blocking events [J]. Journal of Beijing University of Technology, 2019, 45(05): 51-61.
[3] 栾鑫, 邓卫, 程琳, 等. 特大城市居民出行方式选择行为的混合Logit模型[J]. 吉林大学学报(工学版), 2018, 48(4): 1029-1036.
LUAN X, DENG W, CHENG L, et al. Mixed logit model for understanding travel mode choice behavior of megalopolitan residents [J]. Journal of Jilin University (Engineering and Technology Edition), 2018, 48(4): 1029-1036.
[4] 郭季, 罗明杰, 崔姗姗, 等. 基于结构方程模型的城市居民出行方式选择研究[J]. 公路与汽运, 2020(2): 30-35.
[5] 景鹏, 隽志才, 查奇芬. 考虑心理潜变量的出行方式选择行为模型[J]. 中国公路学报, 2014, 27(11): 84-92, 108.
JING P, JUAN Z C, ZHA Q F. Incorporating psychological latent variables into travel mode choice model [J]. China Journal of Highway and Transport, 2014, 27(11): 84-92, 108.
[6] 田晟, 朱泽坤, 许凯. 基于三参考点多属性决策的居民出行方式选择[J]. 广西大学学报(自然科学版), 2019, 44(4): 1207-1214.
TIAN S, ZHU Z K, XU K. Residents’ travel mode choice based on multi-attribute of three reference points decision-making [J]. Journal of Guangxi University (Nat Sci Ed), 2019, 44(4): 1207-1214.
[7] KITAMURA R. An evaluation of activity-based travel analysis [J]. Transportation, 1998, 15(1): 9-34.
[8] KUPPAM A R, PENDYALA R M. A structural equations analysis of commuters' activity and travel patterns [J]. Transportation, 2001, 28(1): 33-54.
[9] LIMTANAKOOL N, DIJST M, SCHWANEN T. The influence of socioeconomic characteristics, land use and travel time considerations on mode choice for medium- and longer-distance trips [J]. Journal of Transport Geography, 2006, 14(5): 327-341.
[10] HUANG C, WANG Y, LI X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China [J]. The Lancet, 2020, 395(10223): 497-506.
[11] CHEN N, ZHOU M, DONG X, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: A descriptive study [J]. The Lancet, 2020, 395(10223): 507-513.
[12] ZHU N, ZHANG D, WANG W, et al. A novel coronavirus from patients with pneumonia in China, 2019 [J]. The New England Journal of Medicine, 2020, 382(8): 727-733.
[13] 梅珊, 何华, 朱一凡. 空气传播传染病城市扩散建模[J]. 管理评论, 2016, 28(8): 158-166.
MEI S, HE H, ZHU Y F. Modeling the spreading of airborne infectious diseases in a city [J]. Management Review, 2016, 28(8): 158-166.
[14] YANG Z F, ZENG Z Q, WANG K, et al. Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions [J]. Journal of Thoracic Disease, 2020, 12(3): 165-174.
[15] WANG F S, ZHANG C. What to do next to control the 2019-nCoV epidemic? [J]. The Lancet, 2020, 395(10222): 391-393.
[16] 薄涛. 疾病预防控制机构突发公共卫生事件应急能力理论与评价研究[D].济南: 山东大学, 2009.
[17] 周继彪, 马昌喜, 董升, 等.新冠肺炎疫情下城市公共交通非常规防疫策略-以宁波市为例[J/OL].中国公路学报, 2020-03-06. doi: https://kns.cnki.net/KCMS/detail/61.1313.U.20200306.1450.004.html.
ZHOU J B, MA C X, DONG S, et al. Unconventional prevention strategies for urban public transport in the COVID-19 epidemic: Taking Ningbo City as a case study[J/OL]. China Journal of Highway and Transport, 2020-03-06. doi: https://kns.cnki.net/KCMS/detail/61.1313.U.20200306.1450.004.html.
[18] 许明星, 郑蕊, 饶俪琳, 等. 妥善应对现于新冠肺炎疫情中“心理台风眼效应”的建议[J]. 中国科学院院刊, 2020, 35(3): 273-282.
XU M X, ZHENG R, RAO L L, et al. Proposals for coping with “psychological typhoon eye” effect detected inCOVID-19 [J]. Bulletin of Chinese Academy of Sciences, 2020, 35(3): 273-282.
[19] 刘远立, 吴依诺, 何鸿恺, 等. 加强我国公共卫生治理体系和治理能力现代化的思考-以科学认识和把握疫情防控的新常态为视角[J]. 行政管理改革, 2020(3): 10-16.
LIU Y L, WU Y N, HE H K, et al. Strengthening the modernization of governing system and capacity of public health in China [J]. Administration Reforms, 2020(3): 10-16.
[20] 茹小磊, 杨超, 严钢, 等.应对突发大规模流行病的城市常规公交管控策略[J/OL].中国公路学报, 2020-05-26. doi: https://kns.cnki.net/kcms/detail/61.1313.U.20200525.1820.002.html.
RU X L, YANG C, YAN G, et al. Control strategy of urban public transit in response to large-scale emergent epidemic[J/OL]. China Journal of Highway and Transport, 2020-05-26. doi: https://kns.cnki.net/kcms/detail/61.1313.U.20200525.1820.002.html.
[21] 李健, 陈田, 张懿木.面向传染病疫情防控的公共交通运行管理决策支持研究[J/OL].中国公路学报, 2020-07-01. doi: https://kns.cnki.net/kcms/detail/61.1313.U.20200630.1736.004.html.
LI J, CHEN T, ZHANG Y M. Research on decision supports of public transport operation management for epidemic prevention and control of infectious diseases[J/OL]. China Journal of Highway and Transport, 2020-07-01. doi: https://kns.cnki.net/kcms/detail/61.1313.U.20200630.1736.004.html
[22] 陈丰, 丁文龙, 叶一芃, 等.公共卫生事件暴发初期的医疗物资调度优化[J/OL]. 中国公路学报, 2020-07-06. doi: https://kns.cnki.net/kcms/detail/61.1313.U.20200706.1101.008.html.
CHEN F, DING W L, YE Y P, et al. Optimal coordination model of medical commodities under the initial stage of outbreak of public health events[J/OL]. China Journal of Highway and Transport, 2020-07-06. doi: https://kns.cnki.net/kcms/detail/61.1313.U.20200706.1101.008.html.
[23] 胡晓伟, 宋浪, 杨滨毓, 等. 重大突发公共卫生事件下城市应急医疗物资优化调度研究[J/OL]. 中国公路学报, 2020-07-08. doi: https://kns.cnki.net/kcms/detail/61.1313.U.20200708.0842.002.html.
HU X W, SONG L, YANG B Y, et al. Research on optimal matching of urban emergency medical supplies under major public health events[J/OL]. China Journal of Highway and Transport, 2020-07-08. doi: https://kns.cnki.net/kcms/detail/61.1313.U.20200708.0842.002.html.
[24] 周文竹.突发公共卫生安全事件下分阶段城市交通应急对策-应对2020新型冠状病毒肺炎突发事件笔谈会[J/OL].城市规划, 2020-02-14. doi: http://kns.cnki.net/kcms/detail/11.2378.TU.20200214.1035.002.html.
[25] 姜楠, 李赛, 曹素珍, 等. 新冠肺炎疫情期间我国人群交通出行行为分析[J]. 环境科学研究, 2020, 33(7): 1675-1682.
JIANG N, LI S, CAO S Z, et al. Transportation activity patterns of Chinese population during the COVID-19 epidemic [J]. Research of Environmental Sciences, 2020, 33(7): 1675-1682.
[26] 葛洪磊, 刘南. 重大传染病疫情演化情境下应急物资配置决策建模分析:以新冠肺炎疫情为例[J]. 管理工程学报, 2020, 34(3): 214-222.
GE H L, LIU N. Modeling of emergency materials allocation decision-making problems based on the evolution scenarios of serious infectious disease: A case of COVID-19 [J]. Journal of Industrial Engineering/Engineering Management, 2020, 34(3): 214-222.
[27] 逯婷婷. 基于多层Nested Logit模型的城市居民出行链预测研究[D]. 北京: 北京交通大学, 2016.
[28] 关志宏.非集计模型-交通行为分析的工具[M]. 北京: 人民出版社, 2004.
[29] 马书红, 付建川, 姚志刚. 基于家庭属性和NestedLogit模型的学生出行选择特性分析[J]. 重庆交通大学学报(自然科学版), 2015(34): 122-127.
MA S H, FU J C, YAO Z G. Choice characteristics of students’ travel behavior based on household characteristics and nested logit model [J]. Journal of Chongqing Jiaotong University (natural science), 2015(34): 122-127.
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