One of the most challenging tasks a city has to continually accomplish to provide ample infrastructure for its inhabitants. It can be difficult, (if not outright costly) to determine what areas need the most attention. While surveys are a useful tool, they are far from an efficient process.
Thanks to new research co-authored by MIT and the Ford Motor Company, there may be a new approach to tackling this problem. By devising a new “computational system that uses cellphone location data to infer urban mobility patterns,” we could be potentially one step closer to identifying urban mobility patterns. From MIT:
“The great advantage of our framework is that it learns mobility features from a large number of users, without having to ask them directly about their mobility choices,” says Marta González, an associate professor of civil and environmental engineering (CEE) at MIT and senior author on the paper. “Based on that, we create individual models to estimate complete daily trajectories of the vast majority of mobile-phone users. Likely, in time, we will see that this brings the comparative advantage of making urban transportation planning faster and smarter and even allows directly communicating recommendations to device users.”
This is a step beyond older methods, which involved gathering relevant data by committee. With the use of cellphone data use, municipalities would have better insight to not only determine current traffic but also use that data to predict future growth. It’s these kinds of insights that may prove invaluable in the long run. Though the study mentioned is focused on the United States, it may have applications on a worldwide scale.
Read the article in full from MIT here.