  The autonomous car technology promises to replace human drivers with safer
driving systems. But although autonomous cars can become safer than human
drivers this is a long process that is going to be refined over time. Before
these vehicles are deployed on urban roads a minimum safety level must be
assured. Since the autonomous car technology is still under development there
is no standard methodology to evaluate such systems. It is important to
completely understand the technology that is being developed to design
efficient means to evaluate it. In this paper we assume safety-critical systems
reliability as a safety measure. We model an autonomous road vehicle as an
intelligent agent and we approach its evaluation from an artificial
intelligence perspective. Our focus is the evaluation of perception and
decision making systems and also to propose a systematic method to evaluate
their integration in the vehicle. We identify critical aspects of the data
dependency from the artificial intelligence state of the art models and we also
propose procedures to reproduce them.
