用8类参数化道路组件生成高多样性路网场景，提升自动驾驶测试真实性。
RoadGen: Generating Road Scenarios for Autonomous Vehicle Testing
- 通过拼接8类参数化道路组件构建复杂路网，实现拓扑与几何多样性。
- 生成的路网在拓扑和几何上均具备高度多样性，满足测试需求。
- 适合自动驾驶仿真测试人员及道路场景生成研究者使用。
随着自动驾驶技术快速发展，基于场景的测试需求日益增长，但道路场景（如道路拓扑与几何）仍缺乏关注。现有方法或仅生成基础道路组件而无法构成完整路网，或虽能生成完整路网但组件过于简单，导致场景多样性不足。为此，本文提出RoadGen，通过连接八类参数化道路组件，系统性生成拓扑与几何多样化的道路场景。评估结果表明，RoadGen在生成多样化道路场景方面具有有效性和实用性，可为自动驾驶仿真测试提供高质量场景支持。
原文摘要 · Abstract (English)
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.
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