Abstract
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.
Highlights
The scenario-based approach for safety validation of highly automated driving (HAD) was presented as a result of the recently finished research projects PEGASUS and ENABLE-S3
The sequential approach presented in this work calculates OLs based on previously generated point cloud (PCL)
The further sections are organized as follows: In Sect. 2, the sequential approach is proposed as consequence of the state of the art limitations and the usage of the relatively new Open Simulation Interface (OSI) data structure within the Functional Mockup Interface (FMI) interface is shown in detail
Summary
The scenario-based approach for safety validation of highly automated driving (HAD) was presented as a result of the recently finished research projects PEGASUS and. As perception plays a central role for HAD, simulation-based testing requires synthetic sensor data of validated fidelity at different processing states or interfaces. While the former is dominated by hardware components, the latter mainly consists of processing algorithms. IF2 is part of the data processing unit before, e.g., object tracking and classification takes place, as
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