Infrastructure, Planning and Environment

In an era of unprecedented global urbanization, urban society is facing a growing demand for mobility, which creates enormous pressure on the urban road networks [1, 2]. As a result, we face severe traffic congestions and increasing fuel consumption that in the long-run increases air pollution. In the short term, however, the increase in traffic loads, alongside the increase in the use of mobile navigation apps, disconnects the natural linkages between traffic planning and land use allocation.

Understanding patterns of growth for cities is a crucial issue for its practical and policy implications e.g. regarding sustainability, but also from a theoretical point of view regarding the validation of theories for urban systems. A particular entry is taken by the Evolutive Urban Theory which postulates interactions between cities as main drivers of their growth.

Digest the complex temporal dynamics of hierarchical communities is hard to attain in a way that captures the changes in rank and size of its members. Particularly, in urban systems, scaling laws and rank clocks approaches have proved to capture much of this dynamic at macro and micro scales respectively, correlating the variation of urban attributes with city size.

In the last decades we observed an increase in the use of microsimulations to tackle real life problems. In all the applications, different models are applied on top of a synthetic static populations. An even more demanding task is to let such static populations to evolve in time.

"The relation between micro-economic activity and space, like the relation between culture and space, is largely mediated by movement" [1].