{"url":"/dataset/highd-dataseth","name":"highD Dataset","full_name":"The Highway Drone Dataset Naturalistic Trajectories of 110 500 Vehicles Recorded at German Highways","description_markdown":"The highD dataset is a new dataset of naturalistic vehicle trajectories recorded on German highways. Using a drone, typical limitations of established traffic data collection methods such as occlusions are overcome by the aerial perspective. Traffic was recorded at six different locations and includes more than 110 500 vehicles. Each vehicle's trajectory, including vehicle type, size and manoeuvres, is automatically extracted. Using state-of-the-art computer vision algorithms, the positioning error is typically less than ten centimeters. Although the dataset was created for the safety validation of highly automated vehicles, it is also suitable for many other tasks such as the analysis of traffic patterns or the parameterization of driver models.","description_withheld":null,"homepage":"https://levelxdata.com/highd-dataset/","introduced_date":"2018-10-11","introduced_date_note":null,"introduced_by":{"paper":"/paper/the-highd-dataset-a-drone-dataset-of","title":"The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems","first_author":"Robert Krajewski","url":null},"license":{"name":"Non-Commercial","url":"https://levelxdata.com/highd-dataset/"},"modalities":[{"name":"Tracking","url":"/datasets/modality/tracking"}],"tasks":[{"name":"Trajectory Prediction","url":"/task/trajectory-prediction","datasets_with_task":"/datasets/task/trajectory-prediction"},{"name":"Trajectory Forecasting","url":"/task/trajectory-forecasting","datasets_with_task":"/datasets/task/trajectory-forecasting"},{"name":"Trajectory Planning","url":"/task/trajectory-planning","datasets_with_task":"/datasets/task/trajectory-planning"},{"name":"Trajectory Modeling","url":"/task/trajectory-modeling","datasets_with_task":"/datasets/task/trajectory-modeling"},{"name":"Trajectory Clustering","url":"/task/trajectory-clustering","datasets_with_task":"/datasets/task/trajectory-clustering"}],"languages":[],"variants":["highD Dataset"],"data_loaders":[{"repo":"https://github.com/woodoxen/tactics2d","url":"https://tactics2d.readthedocs.io/en/latest/","frameworks":[]}],"num_papers_in_archive":115,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}