Bi Weihan, Shen Yu, Ji Yuxiong, Du Yuchuan
Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai, China.
PLoS One. 2025 Sep 3;20(9):e0328700. doi: 10.1371/journal.pone.0328700. eCollection 2025.
The COVID-19 pandemic has caused unprecedented disruptions to individual travel behavior in the public transport (PT) system. To attract more travelers to use PT in the post-pandemic era, it is necessary to understand the heterogeneity of travel behavior changes among various user segments and across different pandemic periods. This paper presents a two-step analysis framework for discovering the inter-segment and intra-segment changes in travel patterns of PT users based on ticketing data. The framework is then applied to the case of Jiading bus transit in Shanghai, China during the COVID-19 pandemic in 2022. The results suggest that commuters are more vulnerable to the impacts of the pandemic than non-commuters, with a considerable tendency to give up commuting by bus or even permanently discontinue bus usage after the lockdown in Shanghai. Only 17.7% of bus users maintain their travel patterns after the lockdown, with a few observable sub-segments of users comprising students and employees. The findings in this study aid PT operators in achieving a better recovery in the post-pandemic era and enhance their preparedness to tackle challenges in demand management for potential crises.
新冠疫情给公共交通(PT)系统中的个人出行行为带来了前所未有的干扰。为了在疫情后时代吸引更多乘客使用公共交通,有必要了解不同用户群体以及不同疫情阶段出行行为变化的异质性。本文提出了一个两步分析框架,用于基于票务数据发现公共交通用户出行模式的段间和段内变化。该框架随后应用于2022年新冠疫情期间中国上海嘉定公交的案例。结果表明,通勤者比非通勤者更容易受到疫情的影响,在上海封控后有相当大的倾向放弃乘坐公交通勤,甚至永久停止使用公交。封控后只有17.7%的公交用户保持其出行模式,有一些可观察到的用户子群体包括学生和员工。本研究的结果有助于公共交通运营商在疫情后时代实现更好的恢复,并增强其应对潜在危机需求管理挑战的准备。