  In this paper, a cooperative decision-making is presented, which is suitable
for intention-aware automated vehicle functions. With an increasing number of
highly automated and autonomous vehicles on public roads, trust is a very
important issue regarding their acceptance in our society. The most challenging
scenarios arise at low driving speeds of these highly automated and autonomous
vehicles, where interactions with vulnerable road users likely occur. Such
interactions must be addressed by the automation of the vehicle. The novelties
of this paper are the adaptation of a general cooperative and shared control
framework to this novel use case and the application of an explicit prediction
model of the pedestrian. An extensive comparison with state-of-the-art
algorithms is provided in a simplified test environment. The results show the
superiority of the proposed model-based algorithm compared to state-of-the-art
solutions and its suitability for real-world applications due to its real-time
capability.
