Community-based research as innovative, ‘intelligent’ transport data

As the world becomes more urbanized, US cities have been experiencing a shift in demographic trends that are reshaping institutional sectors. Exacerbated by the rising home prices in the increasingly expensive urban core, some of public transit’s more reliable riders are being displaced to more affordable, non-coverage areas. This study presents a challenge to the future efficacy and sustainability of traditional fixed-route transit systems as they seek to compete with emerging smart transit alternatives. To better understand how existing transit systems can adapt to the needs created by demographic shifts, it is necessary to examine how broader systemic issues shape community members’ barriers to public transportation and how innovative transit solutions can respond to those barriers. The following research is a case study using data from focus groups conducted with both transit users and non-transit users in a medium-sized Southern city in the United States. The focus groups explored the barriers to public transit use, revealing both structural and cultural factors that contribute to lower ridership. The findings from the focus group were then compared with findings from several microtransit pilots across the country. The results highlight the limitations of microtransit in addressing mobility barriers that result from structural inequities. The comparative findings help illustrate the gaps between current transit innovation projects and the needs of local community members. The results suggest that app-driven data may not be sufficient to capture the nuanced barriers to transit reflected in the lived experiences of community members. Pairing community-based data with app-based data to better understand the needs of a diverse and dynamic rider market can provide innovative directions and solutions for responsive and sustainable future public transit.