Song, Ying

Transit services connect people to jobs and opportunities, fostering vibrant communities and multimodal travel along service corridors. A transit right-of-way (ROW) can help buses bypass congestion and stay on schedule. Many studies have proved that transit ROWs effectively improve service reliability and reduce user costs. However, these studies often focus on one or two service corridors, limiting comprehensive impact assessment. This project addresses this gap by investigating service reliability for all route segments across a transit system. We derived reliability metrics at the route segment level using high-resolution automatic vehicle location (AVL) and automatic passenger count (APC) data collected in the Twin Cities metropolitan area. We then collected and integrated data from various sources via spatial-temporal computing to capture service characteristics, operating environments, traffic conditions, and land-use features along route segments. We applied the Gradient Boosting Model (GBM) to examine nonlinear relationships between these factors and bus travel time reliability. Lastly, we used the trained model to estimate potential improvements in reliability with dedicated ROWs. Through these steps, we worked with members of the Technical Advisory Panel (TAP) to illustrate our methodology and demonstrate its utility for transit agencies. Specifically, the results proved that the ratio of bus lanes and busways was associated with more reliable travel time along route segments. We also found that route segments along a few service corridors with unreliable services can greatly benefit from implementing a dedicated ROW.

Transportation systems, as integral parts of human settlements, reflect the societal structures and cultural ideologies influenced predominantly by the dominant race or class. In the absence of prioritizing the transportation needs of underserved communities, transportation systems may perpetuate systematic inequities. This study aims to address the inequities present in current transportation systems by conducting a comprehensive examination of the transportation experiences of individuals belonging to ten specific underserved communities. These communities include eight within the Twin Cities metropolitan region (Latinx, African American, Hmong, people with disabilities, immigrants, people living with HIV, single mothers, and single fathers), as well as two communities in the Greater Minnesota area (transitioning home residents in Fergus Falls and tribal members of the White Earth Nation). This research adopts a mixed-method approach, incorporating both qualitative interviews and quantitative smartphone-based travel behavior surveys. The findings reveal that each community faces distinct transportation barriers, alongside shared themes in transportation inequities such as inadequate public transportation, difficulties related to car use, and the impact of transportation on significant life outcomes. Recommendations for future research and practice are provided.

Gender can have a significant influence on people’s behaviors and experiences. Hence, excluding gender diversity in transportation research and practices can result in biased or incomplete understandings of issues and perceptions about transportation and quality of life. This study examined whether and how gender, in a broader sense, can result in distinctly different activity-travel patterns and subjective well-being (SWB) outcomes using survey data. The study reviewed existing literature and found that gender was not binary meaning that some gender identities were not solely female or male. The literature also indicated a person’s gender typically intersected with their other social identities such as race and family type and created unique needs and experiences. To address the complex nature of gender, the team collected new data using the Daynamica smartphone application and included specific questions concerning (1) participants’ gender identities and attitudes toward gender roles, (2) their share of household-supporting tasks in 14-day travel diaries, and (3) their emotions during trips and activity participation. The team used 2021 Daynamica survey data and 2019 Travel Behavior Inventory data from the Metropolitan Council to extract activity-travel patterns before and after COVID-19. The team associated these patterns with participants’ gender and other identities and SWB outcomes through visual explorations and statistical analysis. The findings suggested the importance of capturing the complex, intersectional nature of gender, confirmed the persistent existence of gender differences in transportation needs, experiences, and SWB outcomes in Minnesota, and supported continuous efforts and investments to advance gender equity in transportation.