Data from: A model to identify urban traffic congestion hotspots in complex networks

The rapid growth of population in urban areas is jeopardizing the mobility
and air quality worldwide. One of the most notable problems arising is
that of traffic congestion. With the advent of technologies able to sense
real-time data about cities, and its public distribution for analysis, we
are in place to forecast scenarios valuable for improvement and control.
Here, we propose an idealized model, based on the critical phenomena
arising in complex networks, that allows to analytically predict
congestion hotspots in urban environments. Results on real cities’ road
networks, considering, in some experiments, real- traffic data, show that
the proposed model is capable of identifying susceptible junctions that
might becomes hotspots if mobility demand increases.