Lyft Level 5 Dataset

This is a comprehensive, large-scale dataset featuring the raw sensor camera and LiDAR inputs as perceived by a fleet of multiple, high-end, autonomous vehicles in a bounded geographic area. This dataset also includes high quality, human-labelled 3D bounding boxes of traffic agents, an underlying HD spatial semantic map.

This dataset includes a high quality semantic map. A semantic map provides context to reason about the presence and motion of the agents in the scenes. The provided map has over 4000 lane segments (2000 road segment lanes and about 2000 junction lanes) , 197 pedestrian crosswalks, 60 stop signs, 54 parking zones, 8 speed bumps, 11 speed humps. All map elements are registered to an underlying geometric map. This is the same frame of reference for all the scenes in the dataset.

Data is collected by a fleet of Ford Fusion vehicles. Each vehicle is equipped with the following sensors:

LiDARS - One 40-beam roof LiDAR and two 40-beam bumper LiDARs. - Each LiDAR has an azimuth resolution of 0.2 degrees. - All three LiDARs jointly produce ~216,000 points at 10 Hz. - The firing directions of all LiDARs are the same at any given time.

Cameras - Six wide-field-of-view (WFOV) cameras uniformly cover 360 degrees field of view (FOV). Each camera has a resolution of 1224x1024 and a FOV of 70°x60°. - One long-focal-length camera is mounted slightly pointing up primarily for detecting traffic lights. The camera has a resolution of 2048x864 and a FOV of 35°x15°. - Every camera is synchronized with the LiDAR such that the LiDAR beam is at the center of the camera's field of view when the camera is capturing an image.

Data and Resources

Additional Info

Field Value
Source Lyft Level 5
Maintainer Lyft Level 5 team
Associated Tasks 3D object detection; scene depth estimation; scene segmentation; prediction of agents; agent behavior classification
Number of Instances 55,000+ human-labeled 3D annotated frames
Package Description Lyft uses the existing nuScenes format for the dataset to ensure compatibility with existing work that may have been done using the nuScenes dataset. https://www.nuscenes.org/data-format
Dataset has missing values False