When I started my Ph.D. in Boston, I quickly realized how limited and outdated our data is on urban mobility. We often talk about “car dependence,” “walkable neighborhoods,” or “transit equity,” but self-reported surveys that people complete—often outdated by years—usually provide the information behind these terms. These surveys typically ask people to remember every trip they took the day before—which, as you might expect, leads to a lot of missing or inaccurate data.
That insight inspired me—along with my colleagues at Northeastern University and MIT—to develop a new approach: a smartphone-based travel survey that could automatically track people’s movements and uncover the true patterns of how cities function. We named it the BostonWalks Study.
Reimagining the Way We Track Mobility
Smartphones have become powerful tools for sensing everyday activity. They can detect when we start walking, hop on a bus, or pause for a coffee break. By leveraging GPS and motion sensors—always with informed consent and strong privacy protections—we’re able to collect precise, second-by-second data on where people actually go, rather than relying on their memory of past trips.
In 2023, we enlisted nearly a thousand residents from across the Boston metro area. Each person installed a tracking app and used it for at least two weeks, with many continuing for over a month. We collected one of the most detailed mobility datasets ever in North America: over 155,000 trips from 990 participants, covering walking, biking, transit, and driving.
The study—now published in the journal Transportation—also featured a comprehensive survey covering participants’ age, income, race, and household details. This allowed us to analyze how different groups travel and to assess whether certain populations are over- or underrepresented in the transportation data that planners rely on daily.
Our Key Findings
Traditional surveys have consistently underestimated short trips—especially those made on foot. Our data showed that walking actually accounts for about 21% of all trips in Boston, nearly ten times higher than what earlier household surveys suggested. We also found that subway trips made up a much larger share, reflecting the dense, transit-oriented nature of the city’s core.
We discovered some unexpected links between income and travel behavior. Higher-income participants often lived in central, walkable neighborhoods and tended to walk or bike longer distances. In contrast, lower-income participants were more dependent on public transit but typically faced longer, less convenient commutes. We also observed distinct geographic patterns: suburban ZIP codes showed more car-centric travel, while denser, downtown areas saw higher concentrations of biking and walking.
These findings underscore that mobility choices aren’t just personal decisions—they’re shaped by geography, infrastructure, and systemic inequality. Access to reliable transit or safe biking routes isn’t distributed equally, and detailed data like ours can help reveal and address those gaps.
The Difficulty of Earning Trust
Collecting sensitive location data required a thoughtful and careful approach. Every participant provided informed consent, and we encrypted, anonymized, and securely stored all data. Participants had full control over their involvement and could opt out at any time.
Surprisingly, recruiting participants proved more challenging than building the technology itself. We started by reaching out to community organizations but quickly realized that outreach alone wasn’t enough. With help from the Massachusetts Bay Transportation Authority, we launched a poster campaign in subway stations—those recognizable orange-and-white signs seen by daily commuters. That effort reached an estimated 6 million people and helped us meet our recruitment goals.
Despite this, some groups—such as older adults and individuals without smartphones—were still underrepresented. Future studies may need to combine app-based tracking with paper travel diaries or deeper partnerships with community organizations to ensure more inclusive participation.
Why It’s Important
Accurate mobility data is crucial for creating fair and sustainable urban plans. When walking and biking are underestimated, investments in sidewalks, shade trees, and protected bike lanes may be undervalued. Ignoring the lengthy transit commutes faced by low-income households risks deepening existing inequalities.
The BostonWalks study shows that we can gather detailed, real-world travel data at a fraction of the cost of traditional surveys—completing the entire project on a budget under $50,000. This dataset is now openly accessible for researchers and planners interested in exploring issues like transportation equity, emissions, and accessibility.
For me, the most fulfilling aspect has been witnessing how data can inform and drive local policy. Cities everywhere aim to reduce car dependence, lower carbon emissions, and design streets that prioritize people over vehicles. But to transform what we build, we first need a clear understanding of how people actually get around—and with tools like smartphone tracking, that insight is finally attainable.
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