  Car sharing is one the pillars of a smart transportation infrastructure, as
it is expected to reduce traffic congestion, parking demands and pollution in
our cities. From the point of view of demand modelling, car sharing is a weak
signal in the city landscape: only a small percentage of the population uses
it, and thus it is difficult to study reliably with traditional techniques such
as households travel diaries. In this work, we depart from these traditional
approaches and we rely on web-based, digital records about vehicle availability
in 10 European cities for one of the major active car sharing operators. We
discuss how vehicles are used, what are the main characteristics of car sharing
trips, whether events happening in certain areas are predictable or not, and
how the spatio-temporal information about vehicle availability can be used to
infer how different zones in a city are used by customers. We conclude the
paper by presenting a direct application of the analysis of the dataset, aimed
at identifying where to locate maintenance facilities within the car sharing
operational area.
