The large amount of transportation data Didi Chuxing has collected can be used to understand urban traffic conditions and predict the future of urban transportation. Didi Chuxing strives to improve the efficiency of the urban transportation network by providing some of the anonymized data with the academic community.
To download Lyft’s comprehensive, large-scale dataset featuring 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.
Data Garage is an Mcity maintained dataset catalog. We aggregate meta-data about datasets that are produced by Mcity, Mcity members, UM Faculty/Staff, and the industry for search into Data Garage. U-M credentials are required to access the datasets.
The Waymo Open Dataset is comprised of high resolution sensor data collected by Waymo self-driving cars in a wide variety of conditions. The company is releasing this dataset publicly to aid the research community in making advancements in machine perception and self-driving technology.
Waze for Cities Data is available to Waze’s data-sharing partners around the world and includes access to valuable traffic data.