Global communication through mobile phones and on-line activity is a massive phenomenon in urban centers from the entire planet. This generates petabytes of information that contains ﬁngerprints of individual human activity from remote locations. To date, however, it is still missing the link to quantify the individual interaction with streets infrastructures at a city scale. The underlying mechanisms driving the observed trafﬁc ﬂows in modern cities are still less known due to the lack of reliable data and proper methodologies. In this project, we use mobile phone data and road network data to estimate the road usage patterns in the San Francisco Bay area. This ﬁnding enables us to locate the home neighborhoods of road users and ﬁnd how drivers from a particular neighborhood use each road in the city.
Group Member: P. Wang (Postdoc, CEE, MIT)
Collaborators: Prof. A. Bayen (CEE, U.C. Berklee) and Prof. C. Zeegras (DUSP, MIT)
Impact: We learn more properties of the road networks determined by properties based on their usage and to extend the analysis to several cities. This ﬁnding provides an alternative to the expensive travel diaries that can be afforded by only few cities in the world. Our aim is to capture the relation of which roads in the city the population of each small zone use in their daily trips. The obtained information if of paramount importance to plan alternative transportation solutions based on group sharing, such as car sharing alternatives (see Zipcar.com) or ride sharing options (see GoLoco.org).