By collecting the anonymous cellphone location data from nearly two million Bostonians, MIT and Ford were able to produce near-instant urban mobility patterns that typically cost millions of dollars and take years to build.
The big data experiment holds the promise of more accurate and timely data about urban mobility patterns that can be used to quickly determine whether particular attempts to address local transportation needs are working.
In making decisions about infrastructure development and resource allocation, city planners rely on models of how people move through their cities — on foot, in cars and by public transportation. Those models are largely based on socio-demographic information from costly, time-consuming manual surveys, which are in small sample sizes and infrequently updated. Cities might go more than a decade between surveys.