This article provides a field report on how students can acquire simulation know-how while still at university and at the same time learn practice-oriented and interdisciplinary working methods in order to counter the ever-increasing shortage of skilled workers in this field. In order to achieve this goal, a virtual learning factory with the business model of a truck manufactory was founded and set up at a university, which combines the competencies of the participating courses of study so that the individual lectures can be oriented to the common scenarios of the learning factory. One of the main focuses here is the development of autonomous driving functions for the vehicles designed and produced in-house on a scale of 1:14. Various courses of study are involved in this area, for example telematics, business informatics, traffic systems engineering and automation engineering. The vehicles are equipped with the appropriate electronics (3D cameras, lidar sensors, ultrasound, GPS, computer technology and servo motors) and are running with functions using model-based development methods (MATLAB Simulink/Stateflow). The underlying Robotic Operatin System (ROS) connects all components data-technically. As with real vehicle manufacturers, new assistance functions should first be tested in simulation. For this purpose, the present development framework was extended by a traffic simulation, the open source available CARLA (carla.org). During the lectures the students deal with all important aspects around the use and extension of the simulation environment. This includes, for example, the creation of own maps (MathWorks RoadRunner, ASAM OpenDRIVE) of the university campus, the integration of the self-designed vehicles (CATIA 3DEXPERIENCE), the creation of reproducible traffic scenarios (ASAM OpenSCENARIO), the actual testing of MATLAB assistance functions via the integrated ROS bridge, or the development of an own Graphical User Interface (GUI) for the surface-based use of the otherwise Python script-based control of the CARLA environment. The university computer center provides the necessary IT infrastructure, such as a remote WLAN for communication with and between the vehicles, as well as enabling remote access via a protected Virtual Private Network (VPN) or the provision and integration of the on premise CARLA servers. The vehicles and functions of the learning factory evolve here over the semesters, just as they do in real companies, and additional courses of study are successively integrated, taking the learning factory approach to a broader level. In the area of simulation, we are currently working on a collaboration with lectures from the area of operation research. Algorithms from the area of solving classic transport problems are to be connected to the traffic simulation. Currently, the computed nodes and edges are computed in an Open Street Map (OSM) format and shall be transferred to the scenario engine of the CARLA server in the future via the already mentioned ASAM standards OpenDRIVE (the road network) and OpenScenario (the computed routes) as well as export algorithms to be developed accordingly, in order to be able to demonstrate the results of the route planning in a tangible way. This paper focuses on the experiences and best practices in setting up and operating this interdisciplinary learning factory and highlights the achievements in the area of related competence transfer among students.