Journal of Transportation Systems Engineering and Information Technology ›› 2022, Vol. 22 ›› Issue (2): 186-196.DOI: 10.16097/j.cnki.1009-6744.2022.02.018

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Travel Mode Choice Analysis with Shared Mobility in Context of COVID-19

ZHANG Xiao-yu1 , SHAO Chun-fu*1 , WANG Bo-bin2 , HUANG Shi-chen1   

  1. 1. Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, China; 2. Faculty of Science and Engineering, Laval University, Quebec G1V 0A6, Canada
  • Received:2021-12-02 Revised:2022-01-11 Accepted:2022-01-13 Online:2022-04-25 Published:2022-04-23
  • Supported by:
     Fundamental Research Funds for the Central Universities of Ministry of Education of China (2018YJS077);National Natural Science Foundation of China (52072025)



  1. 1. 北京交通大学,综合交通运输大数据应用技术交通运输行业重点实验室,北京 100044; 2. 拉瓦尔大学,科学与工程学院,魁北克G1V 0A6,加拿大
  • 作者简介:张小雨(1995- ),女,山西大同人,博士生
  • 基金资助:

Abstract: To analyze the impact of COVID-19 on the travel mode choice behavior with diverse shared mobility services, this study designed the stated preference (SP) questionnaire for the multi-modal transportation system which include conventional travel modes, ride hailing, ride sharing, car sharing, and bike sharing. The mixed Logit models with panel data were proposed to investigate the travel mode choices before and during COVID-19. The influence differences of explanatory variables are compared, and the joint effects of perceived pandemic severity and mode choice inertia are examined. Based on the elasticity analysis, the mode choice preferences are predicted corresponding to different management policies under COVID-19 pandemic. The results indicate that the perception to pandemic severity has significant impacts on the ridership of ride sharing and car sharing, and the mode choice inertia obviously affects the usage of ride hailing, car sharing, and bike sharing. When the perceived pandemic severity reduces to 30%~ 50%, the strategy of increasing parking charge to 1.6~3.0 times would reduce the usage of private car to pre-pandemic condition, and the car sharing with lower close contact risk could become a main substitute. When the perceived pandemic severity is higher than 60%, the strategy of increasing the travel safety of ride sharing to 1.4~3.6 times would improve the ridership.

Key words: urban traffic, travel mode choice, mixed Logit model, shared mobility, COVID-19, mode choice inertia

摘要: 为分析新冠疫情对共享出行方式选择行为的影响,针对传统出行、网约车、合乘、汽车分时租赁及共享自行车的多方式交通系统设计SP(Stated Preference)问卷;对于疫情前和疫情期间的出行方式选择分别构建基于面板数据的混合Logit模型,比较解释变量的影响差异,分析感知疫情严重程度和方式选择惯性的联合影响;基于弹性分析预测疫情背景下不同管控政策对应的出行方式分担率。结果表明:感知疫情严重程度对合乘和分时租赁影响显著,方式选择惯性对网约车、分时租赁及共享自行车影响显著;当感知疫情严重程度降低至30%~50%时,1.6~3.0倍的停车费调整策略可将私家车分担率降低至疫情前,此时,低密接的分时租赁具有主要替代作用;当感知疫情严重程度在60%以上时,提高合乘出行安全程度至1.4~3.6倍可恢复其分担率。

关键词: 城市交通, 出行方式选择, 混合Logit模型, 共享出行, 新冠疫情, 方式选择惯性

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