The inD dataset is a new dataset of naturalistic vehicle trajectories recorded at German intersections. Using a drone, typical limitations of established traffic data collection methods like occlusions are overcome. Traffic was recorded at four different locations. The trajectory for each road user and its type is extracted. Using state-of-the-art computer vision algorithms, the positional error is typically less than 10 centimetres. The dataset is applicable on many tasks such as road user prediction, driver modeling, scenario-based safety validation of automated driving systems or data-driven development of HAD system components.
For more information please read The inD Dataset: A Drone Dataset of Naturalistic Road User Trajectories at German Intersections.
Not public. From the images published on the official webiste, the annotations seem to be comprised of bounding boxes for vehicles and bounding circles for pedestrians and cyclists.
In order to download the dataset, you must contact the authors and specify your intentions.
No official model has been provided for this dataset.
No official benchmarks have been provided for this dataset.
No associated challenges have been found for this dataset.
Dataset licenced under the Non-Commercial licence.