  As the use of automotive radar increases, performance limitations associated
with radar-to-radar interference will become more significant. In this paper we
employ tools from stochastic geometry to characterize the statistics of radar
interference. Specifically, using two different models for vehicle spacial
distributions, namely, a Poisson point process and a Bernoulli lattice process,
we calculate for each case the interference statistics and obtain analytical
expressions for the probability of successful range estimation. Our study shows
that the regularity of the geometrical model appears to have limited effect on
the interference statistics, and so it is possible to obtain tractable tight
bounds for worst case performance. A technique is proposed for designing the
duty cycle for random spectrum access which optimizes the total performance.
This analytical framework is verified using Monte-Carlo simulations.
