AUTOMATUM DATA: Drone-based highway dataset for the development and validation of automated driving software for research and commercial applications
AUTOMATUM DATA: Drone-based highway dataset for the development and validation of automated driving software for research and commercial applications
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AUTOMATUM DATA：基于无人机的高速公路数据集，用于开发和验证研究和商业应用的自动驾驶软件
DOI：
10.1109/iv48863.2021.9575442
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Kilian Lenz
中科院分区：
文献类型：
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作者：
Paul Spannaus;Peter Zechel;Kilian Lenz
工业和科学领域高度自动化驾驶的最新创新对具有统计意义的现实世界运动数据的逻辑描述产生了日益增长的需求。一方面，这些数据支持软件开发中基于学习的概率方法，另一方面它允许验证和测试。 AUTOMATUM DATA 数据集是一个新数据集，现已在 automatum-data.com 上提供，最初是使用来自 30 小时无人机视频的 12 个典型高速公路场景生成的。用于确定物体轨迹的处理流程已通过参考车辆进行了验证，相对速度误差小于 0.2%。为了生成本研究中描述的数据集，首先对无人机视频中的对象进行识别和分类。然后将检测到的对象与其坐标系结果链接起来，以生成有效的对象轨迹。所提供的数据集可免费用于未来的研究和开发工作（知识共享许可模式 CC BY-ND）。
Recent innovation in highly automated driving in industrial and scientific domains has created a growing demand for logical description of statistically meaningful real-world motion data. On one hand this data supports learning-based probabilistic methods in software development while on the other it allows validation and testing. The AUTOMATUM DATA dataset is a new dataset which is now available at automatum-data.com, and was generated initially using 12 characteristic highway-like scenes from 30 hours of drone videos. The processing pipeline for determining the object trajectories was validated with reference vehicles, where the relative speed error was less than 0.2 percent. To generate the dataset described in this study, the objects from the drone videos were first identified and classified. The detected objects were then linked to their coordinate system results to produce valid object trajectories. The presented dataset is freely available for future research and development-based endeavors (Creative Commons license model CC BY-ND).