openDD: A Large-Scale Roundabout Drone Dataset
This dataset addresses the need for large-scale, annotated trajectory data for traffic analysis in autonomous driving, particularly for roundabouts, but it is incremental as it focuses on data collection rather than new methods.
The authors tackled the challenge of analyzing traffic scenes in autonomous driving by introducing the openDD dataset, which includes 84,774 accurately tracked trajectories and HD map data from seven roundabouts, totaling over 62 hours of data and being the largest publicly available drone-based trajectory dataset.
Analyzing and predicting the traffic scene around the ego vehicle has been one of the key challenges in autonomous driving. Datasets including the trajectories of all road users present in a scene, as well as the underlying road topology are invaluable to analyze the behavior of the different traffic participants. The interaction between the various traffic participants is especially high in intersection types that are not regulated by traffic lights, the most common one being the roundabout. We introduce the openDD dataset, including 84,774 accurately tracked trajectories and HD map data of seven different roundabouts. The openDD dataset is annotated using images taken by a drone in 501 separate flights, totalling in over 62 hours of trajectory data. As of today, openDD is by far the largest publicly available trajectory dataset recorded from a drone perspective, while comparable datasets span 17 hours at most. The data is available, for both commercial and noncommercial use, at: http://www.l3pilot.eu/openDD.