居民活动韧性是社会韧性的重要体现。文中从社会韧性概念出发，定性验证新冠肺炎疫情期间居民活动韧性的存在性，定量分析其演进机制。首先，收集了我国境内28个城市在新冠肺炎疫情发生前后近两年的轨道交通逐日客流数据，定义并测度了居民活动韧性，引入逻辑函数对客流恢复过程进行建模分析；其次，从政策调整与行为适应角度建构并分析政府、公众等多元主体的行动调节和学习适应过程。结果显示，轨道交通网络规模越大的城市，居民活动韧性越高；相较于人口小于500万的城市，人口超过1 000万的超大城市工作日客流恢复到50%、80%、90%和100%水平的时间分别提前7、15、47和95 d，越到恢复后期二者差异越大，周末也呈现出相似的规律。同时，工作日刚性出行相比周末弹性出行具有更强的活动韧性，工作日和周末客流恢复的逻辑函数拟合参数α分别为0.019和0.016，H分别为77.07和106.82 d。在首轮疫情之后的疫情再爆发期间，轨道交通客流下降幅度减小，客流日均恢复率是首轮疫情时的1~3倍，居民活动韧性显著提升。研究认为，科学防控所塑造的公信力提升了公众对管控政策的遵守，公众对风险的认知和学习能显著改善活动韧性。文中研究结果为交通需求及居民活动恢复时间估计、社会管控政策影响评估提供了新的视角。

Urban residents’ activity resilience is a vital component of society resilience. Based on the concept of society resilience, this paper qualitatively verified the existence of urban residents’ activity resilience during the COVID-19 pandemic, and quantitatively analyzed its evolution mechanism. Firstly, by using the daily rail transit ridership data of 28 cities in China in the two years before and after the outbreak of COVID-19, residents’ activity resilience was defined and measured, and a logistic function was introduced to model the ridership recovery process. Secondly, from the perspective of policy adjustment and behavior adaptation, this paper constructed and analyzed the action adjustment and learning adaptation process of plural subjects such as the government and the public. The results show that the larger the scale of rail transit network, the higher the residents’ activity resilience. As compared with the cities with a population of less than 5 million, the time for megacities with a population of more than 10 million to recover to 50%, 80%, 90% and 100% of the weekday ridership is 7 days, 15 days, 47 days and 95 days earlier, respectively. The later the recovery period, the greater the difference, and the weekend also shows a similar pattern. Rigid weekday activities have better resilience than flexible weekend activities, and the logistic function fitting parameters α of ridership recovery on weekdays and weekends are 0.019 and 0.016, respectively; H are 77.07 and 106.82 d, respectively. During the second outbreak after the first round of pandemic, the decline of rail transit ridership decreases, the average daily growth of ridership recovery rate in the second outbreak is 1~3 times that of the first round of pandemic, and residents’ activity resilience improves significantly. It concludes that the credibility created by accurate and effective interventions enhances the public compliance with policies, and that public awareness and learning about risks can significantly improve activity resilience. The research results provide a new perspective on how to estimate the travel demand and activity recovery and evaluate the impact of social interventions.