Amid the impact of COVID-19, the public's willingness to travel has changed, which has had a fundamental impact on the ridership of urban public transport. Usually, travel willingness is mainly analyzed by questionnaire survey, but it needs to reflect the accurate psychological perception of the public entirely. Based on Weibo text data, this paper used natural language processing technology to quantify the public's willingness to travel in the post-COVID-19 era. First, web crawler technology was used to collect microblog text data, which will discuss COVID-19 and travel at the same time. Then, based on the Naive Bayes classification algorithm, travel sentiment analysis was carried out on the data, and the relationship between public travel willingness and urban public transport ridership was analyzed by Spearman correlation analysis. Finally, the LDA topic model was used to conduct content topic research on microblog text data during and after COVID-19. The results showed that the mean values of compelling travel emotion were -0.8197 and -0.0640 during and after COVID-19, respectively. The willingness of the public to travel directly affects the ridership of urban public transport. Compared with the COVID-19 period, the public's fear of travel infection in the post-COVID-19 era has significantly improved, but it still exists. The public pays more attention to the level of COVID-19 prevention and control and the length of travel time on public transport.

As a self-driven travel mode, active travel or active mobility (AT or AM) plays a crucial role in alleviating urban traffic pressure and improving the temporal and spatial irrationality of urban traffic because of its small road occupation area, high mobility and good sustainability. The paper firstly studied the definition and connotation of active mobility. Secondly, starting from the spatiotemporal conditions affecting active mobility, it splited time and space into four types of constraints, namely, departure time, travel time, travel distance and built environment from the perspective of point and line, and expounded the characteristics of different types of spatiotemporal conditions in turn. It also analyzed the potential connection between active mobility and spatiotemporal constraints, and analyzed constraints influence on active mobility with single constraints and multiple spatiotemporal combinations as the entry point. Through summarization, it is found that the influence of spatiotemporal constraints on active mobility is more complicated than that in traditional cognition, and it is mainly a non-linear relationship and some of indexes have corresponding theoretical threshold. Finally, it put forward the shortcomings of the current theoretical research and the future research direction, which will provide a reference for the subsequent research. The purpose of this paper is to summarize the role of spatiotemporal constraints on active mobility, to show the specific change rule of movement travel under the role of different spatiotemporal constraints, aiming at changing the intrinsic thinking of travelers, improving the sharing rate of movement travel, and optimizing the travel structure of urban transportation.