Automated vehicles are about to enter the mass market. However, such systems regularly meet limitations of varying criticality. Even basic tasks such as Object Identification can be challenging, for example, under bad weather or lighting conditions or for (partially) occluded objects. One common approach is to shift control to manual driving in such circumstances, however, post-automation effects can occur in these control transitions. Therefore, we present ORIAS, a system capable of asking the driver to (1) identify/label unrecognized objects or to (2) select an appropriate action to be automatically executed. ORIAS extends the automation capabilities, prevents unnecessary takeovers, and thus reduces post-automation effects. This work defines the capabilities and limitations of ORIAS and presents the results of a study in a driving simulator (N=20). Results indicate high usability and input correctness.