  In this paper we consider a mean field approach to modeling the agents flow
over a transportation network. In particular, beside a standard framework of
mean field games, with controlled dynamics by the agents and costs
mass-distribution dependent, we also consider a path preferences dynamics
obtained as a generalization of the so-called noisy best response dynamics.
Such a preferences dynamics says the agents choose their path having access to
global information about the network congestion state and based on the
observation of the decision of the agents that have preceded. We prove the
existence of a mean field equilibrium obtained as a fixed point of a map over a
suitable set of time-varying mass-distributions, defined edge by edge in the
network. We also address the case where the admissible set of controls is
suitably bounded depending on the mass-distribution on the edge itself.
