{"url":"/dataset/bdd-qa","name":"BDD-QA","full_name":"BDD-QA","description_markdown":"**BDD-QA** is distinguished by its encompassing range of traffic actions, crafted to rigorously evaluate a model's decision-making abilities in traffic scenario. This makes it a potent tool for high-level decision-making research within traffic contexts, including autonomous driving developments.","description_withheld":null,"homepage":"https://github.com/saccharomycetes/text-based-traffic-understanding","introduced_date":"2023-06-05","introduced_date_note":null,"introduced_by":{"paper":"/paper/a-study-of-situational-reasoning-for-traffic","title":"A Study of Situational Reasoning for Traffic Understanding","first_author":"Jiarui Zhang","url":null},"license":null,"modalities":[],"tasks":[{"name":"Question Answering","url":"/task/question-answering","datasets_with_task":"/datasets/task/question-answering"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["BDD-QA"],"data_loaders":[],"num_papers_in_archive":1,"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."}