  This paper proposes a framework to analyze an emerging wireless architecture
where vehicles collect data from devices. Using stochastic geometry, the
devices are modeled by a planar Poisson point process. Independently, roads and
vehicles are modeled by a Poisson line process and a Cox point process,
respectively. For any given time, a vehicle is assumed to communicate with a
roadside device in a disk of radius $ \nu $ centered at the vehicle, which is
referred to as the coverage disk. We study the proposed network by analyzing
its short-term and long-term behaviors based on its space and time performance
metrics, respectively. As short-term analysis, we explicitly derive the
signal-to-interference ratio distribution of the typical vehicle and the area
spectral efficiency of the proposed network. As long-term analysis, we derive
the area fraction of the coverage disks and then compute the latency of the
network by deriving the distribution of the minimum waiting time of a typical
device to be covered by a disk. Leveraging these properties, we analyze various
trade-off relationships and optimize the network utility. We further
investigate these trade-offs using comparison with existing cellular networks.
