With over 13 hours of highly dynamic urban scenarios from autonomous agents and expert drivers, our team is working on research problems ranging from robust sensor fusion, trajectory prediction, dynamic planning and automatic calibration. To learn more about our data and releases, please see the sections below.
In recent years, High Definition (HD) maps have become the core dependency for various state-of-the-art autonomous driving stacks; however, these often require centimeter-level annotations defined manually in order for an autonomous vehicle to be able to identify feasible paths. To motivate research directions using light-weight and fully automated map representations, we present NominalScenes.
More details coming soon.
At AVL, we leverage road furniture for automatic camera calibration. This dataset contains over 5,000 stop signs that have been used to develop our automatic intrinsic calibration pipeline.
More details coming soon.
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