论文标题
为开发和评估汽车感知的LIDAR传感器基准测试
Benchmarking LiDAR Sensors for Development and Evaluation of Automotive Perception
论文作者
论文摘要
环境感知和表示是自动驾驶中最关键的任务。为了满足ISO 26262等安全标准的严格需求，需要对感知到的信息进行有效的定量评估。但是，要使用典型的评估方法，例如使用带注释的数据进行比较，由于涉及的手动工作是不可扩展的。 因此，需要自动数据注释的过程。本文着重于激光雷达传感器，并旨在确定传感器的局限性，并提供了一种生成可测量质量的注释数据的方法。传感器的局限性在对现有学术文本的系统文献综述中进行了分析，并通过与专家的非结构化访谈进行了完善。 主要贡献是1）SLR具有相关的访谈，以识别激光雷达传感器的局限性； 2）相关方法使我们能够生成世界代表。
Environment perception and representation are some of the most critical tasks in automated driving. To meet the stringent needs of safety standards such as ISO 26262 there is a need for efficient quantitative evaluation of the perceived information. However, to use typical methods of evaluation, such as comparing using annotated data, is not scalable due to the manual effort involved. There is thus a need to automate the process of data annotation. This paper focuses on the LiDAR sensor and aims to identify the limitations of the sensor and provides a methodology to generate annotated data of a measurable quality. The limitations with the sensor are analysed in a Systematic Literature Review on available academic texts and refined by unstructured interviews with experts. The main contributions are 1) the SLR with related interviews to identify LiDAR sensor limitations and 2) the associated methodology which allows us to generate world representations.
