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In this paper, a cooperative decision-making is presented, which is suitablefor intention-aware automated vehicle functions. With an increasing number ofhighly automated and autonomous vehicles on public roads, trust is a veryimportant issue regarding their acceptance in our society. The most challengingscenarios arise at low driving speeds of these highly automated and autonomousvehicles, where interactions with vulnerable road users likely occur. Suchinteractions must be addressed by the automation of the vehicle. The noveltiesof this paper are the adaptation of a general cooperative and shared controlframework to this novel use case and the application of an explicit predictionmodel of the pedestrian. An extensive comparison with state-of-the-artalgorithms is provided in a simplified test environment. The results show thesuperiority of the proposed model-based algorithm compared to state-of-the-artsolutions and its suitability for real-world applications due to its real-timecapability.

Cooperative Decision-Making in Shared Spaces: Making Urban Traffic Safer through Human-Machine Cooperation