  One of the challenges related to the investigation of vehicular networks is
associated with predicting a network state regarding both short-term and
long-term network evolutionary changes. This paper analyzes a case in which
vehicles are located on a straight road, and the connectivity state between two
consecutive cars is determined by the Markov chain model with two states. The
transition probabilities of the considered model are explicitly expressed in
terms of known parameters of the network using the Wang-Moayery model. Within
the presented model, the network evolution is described in terms of
determinative parameters, such as average link duration, average cluster
lifetime, and a clusters' existence probability between two fixed moments of
time. In support of the theoretically obtained probabilistic distributions, the
results of numerical simulations are provided.
