Analysing big-data could give city planners better information to help them develop new transport infrastructure, new research suggests.
Researchers from the Massachusetts Institute of Technology (MIT) and car manufacturer Ford Motor Company designed a new computer system that uses mobile phone location data to infer urban mobility patterns.
Applying the system to six weeks of data from residents in Boston (USA), the researchers quickly assembled the kind of model of urban mobility patterns that typically takes years to build.
City planners rely on models on how people move through their cities, on foot, in cars, and on public transport to make decisions about infrastructure development – models largely based on surveys of residents’ travel habits.
However, a broad survey only covers a small percentage of a city’s population. It also takes a long time to conduct a survey and analyse the results.
The new system provides more accurate and timely data about urban mobility and can quickly determine whether measures to address a city’s transport needs are working.
‘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.
For more information, visit mit.edu.