Given the potential benefits of flex-route transit for the environment and traffic congestion, many cities have goals for diffusing flex-route transit. However, previous studies have focused on practical experience, strategic planning, and operational planning of flex-route transit. Few studies have identified the determinants of flex-route transit adoption. This study aims to address the effect of demographic characteristics and psychological factors on flex-route transit adoption by employing a stage of change framework. First, the transtheoretical model is applied to divide respondents into five ordered stages (i.e., Precontemplation, Contemplation, Preparation, Action, and Maintenance). Second, a survey was conducted in Beijing, China, using an online platform to obtain the demographic characteristics and measurement items of the respondents in the five ordered stages. Then, a structural equation model is applied to quantify psychological factors. In addition, the partial proportional odds (PPO) model is employed to estimate the best model and identify the determinants of flex-route transit adoption. Finally, an elasticity analysis is conducted to uncover the effect of determinants on flex-route transit adoption in the five ordered stages. The results suggest that the PPO model has the best fit and validity. The model reveals the significant implications of psychological factors and demographic characteristics for transport policy in various stages. These findings show that, regardless of the initial stage, interventions concentrating on psychological factors and demographic characteristics appear to have the potential to transfer the stage of individuals from one to another. To make policies as effective as possible for promoting flex-route transit adoption, the targeted interventions should be complemented in the specific stage.

Shared bicycle users with commuting purposes generally need to take a traditional public transit and then use the shared bicycle to complete the first/last mile transport. While shared bicycle provides convenient travel for travelers, it also brings a series of problems such as disorderly parking and road occupancy. Therefore, exploring the problem of travel mode shift between shared bicycle and public transit is of significance for improving the traffic environment and increasing the sharing rate of public transit. This paper introduces the flex-route transit system and quantitatively analyzes the rationality and feasibility of using flex-route transit to pick up and drop off shared bicycle users with commuting demand from the temporal perspectives. A flex-route transit route design model is established with the objective of minimizing the sum of vehicle driving time cost and passenger time cost, and the time cost models of the shared bicycle commuting system and the flex-route transit system are constructed, compared, and analyzed to explore the feasibility of flex-route transit picking up or dropping off shared bicycle users under different conditions. Through the subsequent sensitivity analysis, the influence of passenger demand density, fixed station spacing, and travel preference attributed to the two systems are analyzed separately. The results demonstrate that the flex-route transit can efficiently complete the picking up or dropping off for shared bicycle users under certain conditions.

In this paper, to improve the operational service capability and attractiveness of the flex-route transit system, the real dynamic interaction scenario between passenger travel choice preference and system operation scheme in the post-pandemic era is described and quantified. The key technologies, operation mode, system framework, and interactive events required for dynamic interactive scheduling and route planning of flex-route transit are summarized. According to different choice preferences, the corresponding dynamic interaction scheduling strategies and route mixed integer programming model are proposed. An optimization scheme to improve the service capability of the system is introduced and analyzed. The computational results based on real-world cases show that the proposed strategy can better handle the relationship between requirements of transit system operation and requests of passengers without increasing operating costs, significantly improving the service performance of flex-route transit and the choice rate of passengers. We also find that the introduction of optimization schemes and the adjustment of passenger fares constitute a win-win strategy that benefits both passengers and transit operators.

Given the distinct operational features of flex-route transit (FRT) compared to conventional fixed-route systems, this study integrates FRT with urban rail transit and proposes a collaborative optimization approach for feeder flex-route operations and scheduling. The model incorporates path planning, timetable design, and vehicle scheduling to minimize travel costs, enhance operational efficiency, and improve service quality. A mixed-integer nonlinear programming method is applied to optimize scheduling while aligning with rail timetables and passenger transfer behavior. Simulation experiments based on realistic urban transit scenarios are conducted to validate the model, optimizing key operational parameters such as departure intervals, vehicle deployment, and stop selection. The results demonstrate that the proposed approach effectively adjusts schedules and vehicle assignments to accommodate fluctuating passenger demand. This study offers both a theoretical foundation and a practical framework for integrated scheduling of feeder flex-route services, with potential applications for improving coordination and performance in multimodal public transit systems.

In recent years, public bicycles have achieved rapid development around the world. However, public bicycle travel is very sensitive to environmental factors. Weather and climate play a crucial role in users’ choice of bicycle travel. This paper mainly studies the influence of weather and climate factors on the use of public bicycles. Taking Suzhou City as an example, the key factors such as rainfall, temperature, wind scale and Air Quality Index(AQI) level were selected, and the hierarchical linear regression and optimal scale regression were used for comparative analysis: The goodness of fit of optimal scale regression is higher than that of hierarchical regression, so the optimal scale regression result is selected as the final result of this paper. The results showed that rainfall, temperature, wind scale and $A Q I$ level all had significant effects on the number of public bicycle rides in Suzhou. Linear regression model was established, and stepwise regression analysis was used to study the leading and lagging effect of weather factors on urban public bicycle travel volume. The results showed that rainfall variable has leading and lagging effect on the travel volume of public bicycles. The results of this study can provide assistance in alleviating the negative effects of various weather factors on public bicycle travel in various ways.

As populations age, public transit systems face increasing pressure to meet the specific mobility needs and service expectations of elderly passengers. To address these challenges, this study adopts a perception-oriented approach and uses a structural equation model (SEM) to develop an evaluation model for age-friendly public transit. This model integrates refined service attributes with psychological mediating factors and systematically examines how service attributes influence overall satisfaction through both direct and indirect (mediated) pathways. The SEM analysis reveals that three service factors—Adequacy of Age-Friendly Facilities, Service Professionalism, and Environmental Comfort and Convenience—have significant positive effects on overall passenger satisfaction. Meanwhile, two psychological factors—Perceived Safety and Perceived Social Support—emerge as significant mediators linking these service factors to overall satisfaction. Collectively, the findings suggest that improving service quality for elderly passengers requires not only improvements to physical infrastructure and service management, but also attention to psychological pathways related to a sense of safety and emotional connectedness. This underscores the critical role of psychological perceptions in shaping overall satisfaction. Based on these insights, the study outlines targeted, practice-oriented strategies to support future improvements in age-friendly public transit.