Validating safety is an unsolved challenge before autonomous driving on public roads is possible. Since only the use of simulation-based test procedures can lead to an economically viable solution for safety validation, computationally efficient simulation models with validated fidelity are demanded. A central part of the overall simulation tool chain is the simulation of the perception components. In this work, a sequential modular approach for simulation of active perception sensor systems is presented on the example of lidar. It enables the required level of fidelity of synthetic object list data for safety validation using beforehand simulated point clouds. The elaborated framework around the sequential modules provides standardized interfaces packaging for co-simulation such as Open Simulation Interface (OSI) and Functional Mockup Interface (FMI), while providing a new level of modularity, testability, interchangeability, and distributability. The fidelity of the sequential approach is demonstrated on an everyday scenario at an intersection that is performed in reality at first and reproduced in simulation afterwards. The synthetic point cloud is generated by a sensor model with high fidelity and processed by a tracking model afterwards, which, therefore, outputs bounding boxes and trajectories that are close to reality.

Scenario-based virtual testing is seen as a key element to bring the overall safety validation effort for automated driving functions to an economically feasible level. In this work, a generic and modular architecture for simulation of automotive perception sensors is introduced, as part of the overall virtual testing pipeline. It is based on the functional decomposition of real world perception sensors. All interfaces between the individual modules of the model architecture are oriented on internationally recognized standards and therefore facilitate a high degree of interchangeability. In addition, a wrapper framework handles all outer communication and enables a profile-based parameterization of the model, where every profile reflects a specific set of parameters tailored to the specifications and use case of the end user.

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