About

The Waymo Open Dataset is growing!

The Waymo Open Dataset was first launched in August 2019 with a perception dataset comprising high resolution sensor data and labels for 1,950 segments. In March 2021, we expanded the Waymo Open Dataset to also include a motion dataset comprising object trajectories and corresponding 3D maps for 103,354 segments. We have released the Waymo Open Dataset publicly to aid the research community in making advancements in machine perception and autonomous driving technology.

Whatʼs included

Here's what's currently included in our unique Waymo Open Dataset. We plan to continue growing this dataset, so make sure to continue visiting the page for our most recent updates.

Motion Dataset (released March 2021)

  • 103,354, 20s 10Hz segments (over 20 million frames), mined for interesting interactions
  • 574 hours of data
  • Object data
    • 10.8M objects with tracking IDs
    • Labels for 3 object classes - Vehicles, Pedestrians, Cyclists
    • 3D bounding boxes for each object
    • Mined for interesting behaviors and scenarios for behavior prediction research, such as unprotected turns, merges, lane changes, and intersections
    • 3D bounding boxes are generated by a model trained on the Perception Dataset and detailed in our paper: Offboard 3D Object Detection from Point Cloud Sequences
  • Map data
    • 3D map data for each segment
    • Locations include: San Francisco, Phoenix, Mountain View, Los Angeles, Detroit, and Seattle
  • Code

Check out our related paper, Large Scale Interactive Motion Forecasting for Autonomous Driving: The Waymo Open Motion Dataset, for additional details on the dataset and baseline models.

Perception Dataset (released Aug 2019, last updated March 2020)

  • 1,950 segments of 20s each, collected at 10Hz (390,000 frames) in diverse geographies and conditions
  • Sensor data
    • 1 mid-range lidar
    • 4 short-range lidars
    • 5 cameras (front and sides)
    • Synchronized lidar and camera data
    • Lidar to camera projections
    • Sensor calibrations and vehicle poses
  • Labeled data
    • Labels for 4 object classes - Vehicles, Pedestrians, Cyclists, Signs
    • High-quality labels for lidar data in 1,200 segments
    • 12.6M 3D bounding box labels with tracking IDs on lidar data
    • High-quality labels for camera data in 1,000 segments
    • 11.8M 2D bounding box labels with tracking IDs on camera data
  • Code

Check out our related paper, Scalability in Perception for Autonomous Driving: Waymo Open Dataset, for additional details on scale, diversity, and object detection and tracking baselines.


The Waymo Open Dataset is licensed for non-commercial use. You can find the license agreement here.

While this dataset is not reflective of the full capabilities of our systems, and is only a fraction of the data on which Waymo’s autonomous driving system is trained, we believe that for research purposes this large, diverse, and high-quality dataset should be extremely valuable.

Diversity of Geographics

Waymo Open Dataset is collected from a wide variety of places.

Diversity of Conditions

Waymo Open Dataset includes a wide variety of environments, objects and weather conditions.