Every day billions of people move between homes, workplaces, schools and other sites. These movements form complex patterns known as human mobility. Better insight into these patterns can help improve cities, transport systems and emergency planning. Most current models assume similar rules apply to all trips regardless of distance. Researchers at Rensselaer Polytechnic Institute used anonymized mobile phone data to build a new model. Their study, published in the Journal of the Royal Society Interface, explores how people perceive space and time. The idea arose from an image showing nearby streets enlarged and distant places compressed. The team found that people view locations through both physical distance and personal connections. Drawing on ecology, they created a mode-switching model in which movement strategies change with purpose. Analysis of large datasets from the United States and Senegal showed that real mobility networks differ from those produced by classic models. The new approach better matches observed network features such as modularity and path lengths.
