With the rapid development of autonomous vehicles, there is an increasing demand for scenario-based testing to simulate diverse driving scenarios. However, as the base of any driving scenarios, road scenarios (e.g., road topology and geometry) have received little attention by the literature. Despite several advances, they either generate basic road components without a complete road network, or generate a complete road network but with simple road components. The resulting road scenarios lack diversity in both topology and geometry. To address this problem, we propose RoadGen to systematically generate diverse road scenarios. The key idea is to connect eight types of parameterized road components to form road scenarios with high diversity in topology and geometry. Our evaluation has demonstrated the effectiveness and usefulness of RoadGen in generating diverse road scenarios for simulation.

翻译：随着自动驾驶技术的快速发展，基于场景的测试需求日益增长，以模拟多样化的驾驶场景。然而，作为所有驾驶场景的基础，道路场景（如道路拓扑与几何结构）在现有研究中却鲜有关注。尽管已有若干进展，现有方法要么仅生成基础道路组件而无法构成完整路网，要么能生成完整路网但道路组件过于简单，导致生成的道路场景在拓扑与几何结构上均缺乏多样性。为解决这一问题，我们提出RoadGen以系统化生成多样化道路场景。其核心思想是通过连接八类参数化道路组件，构建在拓扑与几何结构上均具有高度多样性的道路场景。评估结果表明，RoadGen在生成多样化仿真道路场景方面具有显著的有效性与实用性。