1Department of Computer Science, University of Exeter, Exeter, UK
2Department of Physics and Astronomy, University of Rochester, Rochester, NY 14627, USA.
3Department of Computer Science, University of Rochester, Rochester, NY 14627, USA.
4School of Mathematical Sciences, Queen Mary University of London,Mile End Road, E1 4NS, London, UK
5Google Inc., 1600 Amphitheatre Parkway, Mountain View, CA 94043, USA.
6Instituto de Física Interdisciplinar y Sistemas Complejos IFISC (CSIC-UIB), Palma de Mallorca, Spain.
|Given the rapid recent trend of urbanization, a better understanding of how urban infrastructure mediates socioeconomic interactions and economic systems is of vital importance. While the accessibility of location-enabled devices as well as large-scale datasets of human activities, has fueled significant advances in our understanding, there is little agreement on the linkage between socioeconomic status and its influence on movement patterns, in particular, the role of inequality. Here, we analyze a heavily aggregated and anonymized summary of global mobility and investigate the relationships between socioeconomic status and mobility across a hundred cities in the US and Brazil. We uncover two types of relationships, finding either a clear connection or little-to-no interdependencies. The former tend to be characterized by low levels of public transportation usage, inequitable access to basic amenities and services, and segregated clusters of communities in terms of income, with the latter class showing the opposite trends. Our findings provide useful lessons in designing urban habitats that serve the larger interests of all inhabitants irrespective of their economic status.|