  In this paper, we extend some ideas of statistical physics to describe the
properties of human mobility. From a physical point of view, we consider the
statistical empirical laws of private cars mobility, taking advantage of a GPS
database which contains a sampling of the individual trajectories of 2% of the
whole vehicle population in an Italian region. Our aim is to discover possible
"universal laws" that can be related to the dynamical cognitive features of
individuals. Analyzing the empirical trip length distribution we study if the
travel time can be used as universal cost function in a mesoscopic model of
mobility. We discuss the implications of the elapsed times distribution between
successive trips that shows an underlying Benford's law, and we study the rank
distribution of the average visitation frequency to understand how people
organize their daily agenda. We also propose simple stochastic models to
suggest possible explanations of the empirical observations and we compare our
results with analogous results on statistical properties of human mobility
presented in the literature.
