  Autonomous systems control many tasks in our daily lives. To increase trust
in those systems and safety of the interaction between humans and autonomous
systems, the system behaviour and reasons for autonomous decision should be
explained to users, experts and public authorities. One way to provide such
explanations is to use behavioural models to generate context- and
user-specific explanations at run-time. However, this comes at the cost of
higher modelling effort as additional models need to be constructed. In this
paper, we propose a high-level process to extract such explanation models from
system models, and to subsequently refine these towards specific users,
explanation purposes and situations. By this, we enable the reuse of
specification models for integrating self-explanation capabilities into
systems. We showcase our approach using a running example from the autonomous
driving domain.
