Using case-based reasoning for autonomous vehicle guidance

Vehicle guidance in complex scenarios such as inner-city traffic requires an in-depth understanding of the current situation. In order to select the appropriate behavior for an autonomous vehicle, an analysis of the situation is needed. The analysis consists of an estimation of the situation's development with respect to the selected behavior. This can only be done using higher-level reasoning techniques. In this paper, an approach for situation interpretation for autonomous vehicles is presented. The approach relies on case-based reasoning in order to predict the evolvement of the current situation and to select the appropriate behavior. Case-based reasoning allows to utilize prior experiences in the task of situation assessment.