The popularity of environment simulations for fast assessment of autonomous driving functions is growing faster than ever before. But the creation of virtual environments to simulate real driving scenarios remains a challenge. Modeling objects by hand is a rather slow and expensive process. An alternative approach is procedural generation. Unfortunately, most methods produce only fictional environments. In this paper, we present a novel approach to procedurally generate environments for automotive simulations, that are based on real environment recordings and adress physical sensor specific reflection mechanisms. We use OpenDRIVE to generate the layout and road network and augment it with open source data from OpenStreetMap for objects surrounding the road. In addition, we present a workflow for rapid reconstruction of building facades, which allows us to create realistic and immersive environments for simulations. Our approach is based on the Unreal Engine 4, making it compatible with other popular automotive simulation platforms such as CARLA. These generated environments can provide a cost-effective and flexible alternative to physical testing, allowing researchers and developers to simulate different scenarios in a controlled and reproducible environment. Our approach has the potential to significantly improve the efficiency and scalability of automotive simulations by generating realistic environments for simulation purposes. The GitHub repository of this plugin is publicly available on https://github.com/fzi-forschungszentrum-informatik/eg4u.