  The next generations of vehicles are expected to be equipped with
sophisticated sensors to support advanced automotive services. The large volume
of data generated by such applications will likely put a strain on the
vehicular communication technologies, which may be unable to guarantee the
required quality of service. In this scenario, it is fundamental to assess the
value of information (VoI) provided by each data source, to prioritize the
transmissions that have greatest importance for the target applications. In
this paper, we characterize VoI in future vehicular networks, and investigate
efficient data dissemination methods to tackle capacity issues. Through a
simulation study, we show how analytic hierarchy multicriteria decision
processes can be exploited to determine the value of sensory observations as a
function of space, time, and quality criteria.
