  Car traffic in urban systems has been studied intensely in past decades but
models are either limited to a specific aspect of traffic or applied to a
specific region. Despite the importance and urgency of the problem we have a
poor theoretical understanding of the parameters controlling urban car use and
congestion. Here, we combine economical and transport ingredients into a
statistical physics approach and propose a generic model that predicts for
different cities the share of car drivers, the $CO_2$ emitted by cars and the
average commuting time. We confirm these analytical predictions on 25 major
urban areas in the world, and our results suggest that urban density is not the
most relevant variable controlling car-related quantities but rather are the
city's area size and the density of public transport. Mitigating the traffic
(and its effect such as $CO_2$ emissions) can then be obtained by reducing the
urbanized area size or, more realistically, by improving either the public
transport density or its access. In particular, increasing the population
density is a good idea only if it also increases the fraction of individuals
having access to public transport.
