  Probability distributions of human displacements has been fit with
exponentially truncated L\'evy flights or fat tailed Pareto inverse power law
probability distributions. Thus, people usually stay within a given location
(for example, the city of residence), but with a non-vanishing frequency they
visit nearby or far locations too. Herein, we show that an important empirical
distribution of human displacements (range: from 1 to 1000 km) can be well fit
by three consecutive Pareto distributions with simple integer exponents equal
to 1, 2 and ($\gtrapprox$) 3. These three exponents correspond to three
displacement range zones of about 1 km $\lesssim \Delta r \lesssim$ 10 km, 10
km $\lesssim \Delta r \lesssim$ 300 km and 300 km $\lesssim \Delta r \lesssim $
1000 km, respectively. These three zones can be geographically and physically
well determined as displacements within a city, visits to nearby cities that
may occur within just one-day trips, and visit to far locations that may
require multi-days trips. The incremental integer values of the three exponents
can be easily explained with a three-scale mobility cost/benefit model for
human displacements based on simple geometrical constrains. Essentially, people
would divide the space into three major regions (close, medium and far
distances) and would assume that the travel benefits are randomly/uniformly
distributed mostly only within specific urban-like areas.
