  Currently, the most prevalent way to evaluate an autonomous vehicle is to
directly test it on the public road. However, because of recent accidents
caused by autonomous vehicles, it becomes controversial about whether on-road
tests should be the best approach. Alternatively, people use test tracks or
simulation to assess the safety of autonomous vehicles. These approaches are
time-efficient and less costly, however, their credibility varies. In this
paper, we propose to use a co-Kriging model to synthesize the results from
different evaluation approaches, which allows us to fully utilize the
information and provides an accurate, affordable, and safe way to assess a
design of an autonomous vehicle.
