  The behavior of cyclists when choosing the path to follow along a road
network is not uniform. Some of them are mostly interested in minimizing the
travelled distance, but some others may also take into account other features
such as safety of the roads or pollution. Individuating the different groups of
users, estimating the numerical consistency of each of these groups, and
reporting the weights assigned by each group to different characteristics of
the road network, is quite relevant. Indeed, when decision makers need to
assign some budget for infrastructural interventions, they need to know the
impact of their decisions, and this is strictly related to the way users
perceive different features of the road network. In this paper, we propose an
optimization approach to detect the weights assigned to different road features
by various user groups, leveraging knowledge of the true paths followed by
them, accessible, for example, through data collected by bike-sharing services.
