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Ford has announced it’s releasing a comprehensive self-driving vehicle dataset to the academic and research community. The dataset includes not only LiDAR and camera sensor data, GPS and trajectory information, but also unique elements such as multi-vehicle data and 3D point cloud and ground reflectivity maps.

It includes seasonal variations and varied environments throughout Metro Detroit. It features data from sunny, cloudy and snowy days, not to mention freeways, tunnels, residential complexes and neighbourhoods, airports and dense urban areas.

Ford says this effort is to not only improve the way self-driving vehicles navigate their environment and interact with personal cars, pedestrians and other self-driving vehicles, but also to support the next generation of engineers.

Writing in a blog, Tony Lockwood, Autonomous Vehicle Manager, Virtual Driver Systems, Ford Motor Company, says: “In addition to releasing 3D point cloud maps from our LiDAR, we are also giving the research community access to high-resolution 3D ground plane reflectivity maps. Together, these maps give researchers a comprehensive understanding of what our self-driving vehicles “see” in the world around them.”

Ford says the first set of data logs is already available, and we will continue updating the site until all its logs have been uploaded.

To find out more about Ford’s self-driving data package by visit

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