To date, there are at least 9 well-known open datasets on autonomous driving, the earliest released being KITTI by Karlsruhe Institute of Technology and the latest being the Waymo Open Dataset released on August 2019. Other organizations that released open datasets in 2019 include Aptiv (previously Nutonomy) with the nuScenes dataset, Argo with the Argoverse dataset and Lyft with their Level 5 Dataset. In 2018, Berkeley A.I. Research (B.A.I.R), released the BDD100K dataset which is the largest to date in terms of monocular video data frames (120 million frames). Baidu's Apollo program released the ApolloScape dataset which featured 146,997 frames. Hesai & Scale is expected to release their full dataset in the coming months.
Types of data released
The earlier datasets such as the BBD100K and ApolloScape contained primarily annotated frames from monocular camera video. The datasets released in 2019 come in richer variety and include different types of data from LiDAR cameras, radar and stereo cameras. Most of these datasets provide different city scenarios, multiple weather conditions, times of day and scene types to help researchers improve their autonomous driving models and algorithms to work optimally in different situations. The bulk of the datasets are collected from U.S. cities such as San Francisco, Phoenix, Pittsburgh, New York and others, as well as overseas cities in Singapore, Germany (Karlsruhe) and China.
This is a supporting list for the INSIGHTS article 2019 Autonomous Driving Open Datasets Released To Date (url below).