As automation in the field of automated driving (AD) progresses, ensuring the safety and functionality of AD functions (ADFs) becomes crucial. Virtual scenario-based testing has emerged as a prevalent method for evaluating these systems, allowing for a wider range of testing environments and reproducibility of results. This approach involves AD-equipped test vehicles operating within predefined scenarios to achieve specific driving objectives. To comprehensively assess the impact of road network properties on the performance of an ADF, varying parameters such as intersection angle, curvature and lane width is essential. However, covering all potential scenarios is impractical, necessitating the identification of feasible parameter ranges and automated generation of corresponding road networks for simulation. Automating the workflow of road network generation, parameter variation, simulation, and evaluation leads to a comprehensive understanding of an ADF's behavior in diverse road network conditions. This paper aims to investigate the influence of road network parameters on the performance of a prototypical ADF through virtual scenario-based testing, ultimately advocating the importance of road topology in assuring safety and reliability of ADFs.

翻译：随着自动驾驶（AD）领域自动化程度的提升，确保自动驾驶功能（ADF）的安全性与功能性变得至关重要。基于虚拟场景的测试已成为评估这些系统的普遍方法，其能够提供更广泛的测试环境并保证结果的可复现性。该方法涉及配备AD功能的测试车辆在预定义场景中运行，以实现特定的驾驶目标。为全面评估路网特性对ADF性能的影响，改变交叉口角度、曲率和车道宽度等参数至关重要。然而，覆盖所有潜在场景并不现实，因此需要确定可行的参数范围，并自动生成相应的路网进行仿真。将路网生成、参数变化、仿真与评估的工作流程自动化，有助于全面理解ADF在不同路网条件下的行为。本文旨在通过基于虚拟场景的测试，研究路网参数对原型ADF性能的影响，最终论证路网拓扑结构在保障ADF安全性与可靠性方面的重要性。