论文标题
基于高清图分析的道路网络变化，用于自动化车辆的模拟安全保证
Road Network Variation Based on HD Map Analysis for the Simulative Safety Assurance of Automated Vehicles
论文作者
论文摘要
自动驾驶功能（ADF）的验证和验证是使这些功能在当前研究环境之外向公众提供的旅程的一项艰巨任务。模拟是基于方案的测试的宝贵构建块，可以帮助建模与ADF相关的流量情况。除了测试ADF的周围交通和环境外，逻辑描述和自动化的混凝土道路网络还具有重要作用。我们旨在减少手动图生成的努力，并在开发过程中改善自动化测试过程。 因此，本文提出了一种分析真实道路网络并提取相关参数的方法，以使合成仿真图的变化与现实世界属性相对应。因此，从这里的高清图中选择了市内连接的特征。然后，确定，分析和用于在OpenDrive标准中生成道路网络的变化。提出的方法可实现有效的道路网络建模，可用于大规模模拟。开发的道路网络生成工具可在Github上公开获得。
The validation and verification of automated driving functions (ADFs) is a challenging task on the journey of making those functions available to the public beyond the current research context. Simulation is a valuable building block for scenario-based testing that can help to model traffic situations that are relevant for ADFs. In addition to the surrounding traffic and environment of the ADF under test, the logical description and automated generation of concrete road networks have an important role. We aim to reduce efforts for manual map generation and to improve the automated testing process during development. Hence, this paper proposes a method to analyze real road networks and extract relevant parameters for the variation of synthetic simulation maps that correspond to real-world properties. Consequently, characteristics for inner-city junctions are selected from Here HD map. Then, parameter distributions are determined, analyzed and used to generate variations of road networks in the OpenDRIVE standard. The presented methodology enables efficient road network modeling which can be used for large scale simulations. The developed road network generation tool is publicly available on GitHub.
