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Data / ML, Engineering

Power On: Accelerating Uber’s Self-Driving Vehicle Development with Data

June 4, 2019 / Global
Featured image for Power On: Accelerating Uber’s Self-Driving Vehicle Development with Data
Figure 1. Uber ATG leverages data-driven insights to ensure that our technologies facilitate safe interactions between pedestrians and self-driving vehicles.
Figure 2. Uber ATG visualizes two views of our self-driving vehicles driving in different areas. The white dots illustrate where the self-driving vehicle drove while the colored dots visualize pedestrian movement.
Figure 3. Self-driving vehicles intake data while driving to detect pedestrians (time accelerated).
Figure 4. Analysis of pedestrian detections in aggregate show areas with more pedestrians on average (taller bars indicate more pedestrian activity).
Figure 5: Pass/fail results of hundreds of simulated scenario variations displayed across three dimensions.
Figure 6: Using data visualization tools, we can track the self-driving vehicle in 2D and 3D at the track.
Figure 7: Each self-driving vehicle contains a map of the city, generated from the data we gathered previously showing it the lanes available on each road segment. These lanes are colored by volume of pedestrian activity.
Steffon Davis

Steffon Davis

Steffon Davis is a product manager with Uber's Advanced Technologies Group, working on the development of self-driving vehicles.

Posted by Steffon Davis