An immense test space is pushing the development and testing of automated driving functions from real to virtual environments. The virtual world is provided by interconnected simulation models representing sensors, vehicle dynamics, and both static and dynamic environment. For the virtual validation of automated driving, special attention must be paid to the simulation’s credibility, which can be impaired by inappropriate or inaccurate simulation models and tools. Therefore, in this work a method is proposed to assess the credibility of simulation-based testing for automated driving. The approach allows a qualitative and relatively quantitative comparisons between scenarios as well as between different simulation setups. Therefore, several uni- and multivariate metrics are applied towards a scoring of similarity of the behavior between simulation and real test drive. This is achieved by using ground truth data in form of simulation scenarios from real world measurement data. In this way, the virtual automated vehicle encounters the same conditions and surroundings than its counterpart in the real world for evaluating their similarity. The practical applicability of the proposed credibility assessment approach is demonstrated in a case study, in which the credibility of an exemplary simulation-based test bench is inferred.

中文翻译：

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自动驾驶功能场景虚拟测试可信度评估方法


巨大的测试空间正在推动自动驾驶功能的开发和测试从真实环境转向虚拟环境。虚拟世界由代表传感器、车辆动力学以及静态和动态环境的互连仿真模型提供。对于自动驾驶的虚拟验证，必须特别注意仿真的可信度，不适当或不准确的仿真模型和工具可能会损害仿真的可信度。因此，在这项工作中提出了一种方法来评估基于模拟的自动驾驶测试的可信度。该方法允许在场景之间以及不同的模拟设置之间进行定性和相对定量的比较。因此，一些单变量和多变量指标被应用于对模拟和真实试驾之间的行为相似性进行评分。这是通过使用来自现实世界测量数据的模拟场景形式的地面实况数据来实现的。通过这种方式，虚拟自动车辆会遇到与现实世界中的车辆相同的条件和环境，以评估它们的相似性。所提出的可信度评估方法的实际适用性在案例研究中得到了证明，其中推断了示例性基于仿真的测试台的可信度。