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UMD AI Study Aims to Ensure Transit Options Don’t Create One-Way Ticket to Rising Rents

System Will Pinpoint Likely Sites of Tenant Displacement

Manchester Place station under construction May 2025 1920x1080

Crews construct the Purple Line's Manchester Place station in Silver Spring earlier this year. UMD researchers are developing an AI tool to help prevent community members near the stations from being priced out of the rental market as a result of new transit options. (Photo courtesy of Wikimedia Commons)

As construction on the light-rail Purple Line continues between Montgomery and Prince George’s counties, University of Maryland researchers are helping to ensure that lower-income renters can continue living close enough to share in its benefits.

Researchers at UMD’s National Center for Smart Growth (NCSG) are building a database of privately owned apartment properties in the 16-mile Purple Line corridor that charge market-rate rents considered affordable to lower- and middle-income people. The database also captures other factors that suggest “unstable” housing, such as apartment buildings that are older and in need of frequent repairs, or have relatively high eviction rates.

Using artificial intelligence tools, the researchers are training a computer model to predict which apartment properties are most at risk of pricing out tenants if their rent rises significantly, as routinely occurs around new transit stations. The model, which the researchers will continue to refine with new data from community partners, can also predict which apartments are unstable because of poor living conditions or a lack of investment, and therefore at risk of being replaced with higher-end development. 

Nonprofits and community groups can then use the data to help protect tenants from losing their homes to higher rents, eviction or unhealthy living conditions. That could mean helping them lobby landlords for protections and supporting landlords willing to seek government aid to upgrade their buildings in exchange for keeping rents stable. Local officials, meanwhile, could consider the data when exploring policies to encourage construction of more affordable units and preserve those already there.

Assistant Research Professor Chester Harvey, NCSG’s director of data science, cited the “powerful” use of predictive analytics to help people stay in their homes.

“We're asking a computer to assist us in identifying places where we as humans should intervene,” he said.

The state-led Purple Line, which is scheduled to begin carrying passengers in late 2027, is expected to transform how people get to and around D.C.’s northeastern suburbs, including UMD. Five of the 21 stops on the 16.2-mile route linking Bethesda and New Carrollton will be on or near campus. Faculty, staff and students will ride for free between the five campus-area stops and can take the line to Metro, Amtrak and MARC commuter rail stations.

NCSG’s focus on housing instability in the Purple Line corridor comes as Montgomery and Prince George’s, like much of the country, struggle with a severe housing shortage that has sent home prices and rents soaring. A 2024 Redfin study found that the Washington metro area posted the highest annual rent increase in the nation, up 12% to $2,088. 

While expanding transit lines is often key to planning thriving and sustainable communities, doing so can bring unintentional consequences, especially amid a housing crisis: As land and properties near transit stations become more valuable, rents and home prices in surrounding communities often climb even higher.

Meanwhile, renters who might worry about being displaced often don’t know how to best protect themselves, said NCSG Director Kate Howell.

“They’ll say, ‘We want to stay, but how does that work?’” Howell said.

The NCSG database and AI system, funded by a $200,000 grant from the U.S. Department of Housing and Urban Development, covers apartment properties within a mile of the Purple Line corridor. 

As of 2019, the corridor had 17,000 rental units within a mile considered affordable to a family earning $72,000, said Nick Finio, NCSG’s associate director. If that number doesn’t grow – and especially if it significantly shrinks – Maryland’s D.C. suburbs could end up with relatively few affordable places to live, he said. 

Affordable housing advocates say the data has already proven helpful. 

Laura Searfoss of Enterprise Community Partners, which works to increase affordable housing nationwide, said knowing which buildings are home to tenants most at risk of displacement has helped the organization target its efforts.

“We can be really tactical about how we think about preserving these properties,” Searfoss said.

The researchers said they hope their Purple Line work could soon help protect renters in communities around current and future transit lines across Maryland and elsewhere—even in locations with less abundant data across the country. Those include areas around future Flash Bus Rapid Transit stations, the planned Red Line light-rail project in Baltimore and Blue Line Metro stations in Prince George’s.

“That really makes this an incredibly exciting prospect and something that I think is actually impactful and responsive,” Howell said. 

AI at Maryland

The University of Maryland is shaping the future of artificial intelligence by forging solutions to the world’s most pressing issues through collaborative research, training the leaders of an AI-infused workforce and applying AI to strengthen our economy and communities.

Read more about how UMD embraces AI’s potential for the public good—without losing sight of the human values that power it.

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