$2.35M NSF Grant Aims to Ease Transportation for Low-income Baltimore Neighborhoods
A $2.35 million National Science Foundation grant is funding a study based in Baltimore to provide better public transit options to low-income neighborhood residents, who frequently face long commutes with multiple transfers.
Public transit is sometimes touted as an urban planning cure-all, but too often, the outcomes look different depending on income. Affluent city dwellers may find it convenient to board a Metro train or a bus steps from home and alight near their workplaces, but working-class or low-income transit users are more likely to face multiple transfers, long waits and complex routes.
Now, a multidisciplinary team of University of Maryland researchers is partnering with public officials, transit advocacy groups and other universities on a Baltimore-based project designed to make transit planning work for all, particularly those in low-income neighborhoods that rely on bus and light-rail systems.
Be an Advocate for pubLic TransportatiOn (BALTO) joins UMD faculty from the College of Information Studies (iSchool) and the School of Architecture, Planning and Preservation with researchers at Morgan State University and the University of Baltimore. Together, they will create a “digital toolkit” to identify the everyday transit challenges facing low-income residents in eight Baltimore neighborhoods and model the impacts of potential solutions, such as more frequent bus routes or additional stops.
The four-year project launching tomorrow is funded by a $2.35 million grant from the National Science Foundation (NSF) Smart and Connected Communities Program (SCC). It builds on the team’s 2017 SCC planning grant also funded by the NSF, which identified barriers to technology, transportation and opportunity in West Baltimore.
One goal of the NSF-funded project is to identify and address socioeconomic disparities within large public transit systems, said Vanessa Frias-Martinez, an associate professor in the iSchool and principal investigator of the project.
“With the information supplied by our digital toolkit, city and state transit officials will be able to better engage residents in a collaborative effort to understand the geographic mobility challenges of those with limited means, and then take steps to address these challenges,” said Frias-Martinez, who has a joint appointment with the University Maryland Institute for Advanced Computer Studies.
Using volunteer mobility data and input from 1,000 Baltimore residents, researchers will use data analysis and machine learning to identify specific patterns, gaps in service and problem areas, arming stakeholders with the critical information they need for developing block-level solutions.
“This project gives a voice to those who are often not heard in the decision-making process,” said Sevgi Erdogan, an assistant research professor in UMD’s School of Architecture, Planning and Preservation and a co-principal investigator on the project. “Traditional transportation models don't take into account multi-modal experiences, which are commonplace in marginalized and low-income communities, so they cannot identify the sort of mobility obstacles facing individuals.”
When neighborhood residents or others make transit recommendations such as adding a bus stop or tweaking a route, a mobility simulator will model how those interventions will change mobility in a one neighborhood as well as the transit system as a whole.
“We need to view these performance metrics through an equity lens,” said Celeste Chavis, an associate professor in the Department of Transportation and Urban Infrastructure Studies at Morgan State University and a co-PI on the project. “While an Uber can whisk commuters to their destinations, it’s often untenable for those with limited incomes. And the subway system isn’t a good option for people who work off-hours. Better user data can help us identify solutions.”
Two Baltimore-based transit advocacy groups, the Central Maryland Transportation Alliance and Baltimore Transit Equity Coalition, will assist the Housing Authority of Baltimore City in the recruitment of residents from lower-socioeconomic neighborhoods to take part in the study.
Other co-principal investigators include Christopher Antoun, an assistant research professor in the iSchool; Jessica Vitak, an associate professor in the iSchool; and Seema Iyer, a research assistant professor in the Jacob France Institute at the University of Baltimore.
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