MIT Researchers Map NYC Foot Traffic at Scale
Researchers at MIT have mapped New York City's foot traffic at scale for the first time, using anonymized phone and sensor data. The dataset offers granular insights into urban mobility patterns. This development is expected to inform a new generation of tools for retail site selection, out-of-home advertising, and urban planning.
- The model was developed by a team led by Andres Sevtsuk, an associate professor in MIT's Department of Urban Studies and Planning and head of the City Design and Development Group. This initiative marks the first comprehensive model of pedestrian activity for an entire U.S. city, mapping all its sidewalks, crosswalks, and footpaths. - To build and calibrate the model, researchers utilized pedestrian count data from 2018 and 2019, which was collected by New York City's Department of Transportation for up to 1,000 sidewalk segments on weekdays. - The data revealed that Midtown Manhattan has the highest pedestrian density, with an average of 1,697 pedestrians per sidewalk segment per hour during the evening peak. The financial district and Greenwich Village followed, with 740 and 656 pedestrians per hour, respectively. - A key insight from the study is the identification of significant foot traffic in boroughs outside of Manhattan, suggesting a potential "Manhattan bias" in pedestrian infrastructure investment that this data could help rectify. - One of the model's novel applications is its ability to calculate vehicle-pedestrian crashes on a per-pedestrian basis, offering a more accurate risk assessment than just raw crash totals. This helps to identify genuinely dangerous intersections that may not be in the highest traffic areas. - In New York City, 41% of all trips are made on foot, compared to just 28% by vehicle, highlighting the importance of understanding and planning for pedestrian mobility. - The research is already being adapted for other major cities; for example, a similar model is being developed for Los Angeles to aid in planning for the 2028 Olympics. The model has also been applied to over 140 municipalities in Maine. - This work is part of a broader effort by MIT's Senseable City Lab, directed by Carlo Ratti, which explores how digital technologies and data can be used to understand and improve urban environments.
