  Game engines are increasingly used as simulation platforms by the autonomous
vehicle (AV) community to develop vehicle control systems and test
environments. A key requirement for simulation-based development and
verification is determinism, since a deterministic process will always produce
the same output given the same initial conditions and event history. Thus, in a
deterministic simulation environment, tests are rendered repeatable and yield
simulation results that are trustworthy and straightforward to debug. However,
game engines are seldom deterministic. This paper reviews and identifies the
potential causes of non-deterministic behaviours in game engines. A case study
using CARLA, an open-source autonomous driving simulation environment powered
by Unreal Engine, is presented to highlight its inherent shortcomings in
providing sufficient precision in experimental results. Different
configurations and utilisations of the software and hardware are explored to
determine an operational domain where the simulation precision is sufficiently
low i.e.\ variance between repeated executions becomes negligible for
development and testing work. Finally, a method of a general nature is
proposed, that can be used to find the domains of permissible variance in game
engine simulations for any given system configuration.
