Silicon Valley startup Civil Maps creates detailed street-level maps of cities using vector-based graphics, letting cars determine their position based on distance to known objects.
Startup Civil Maps today announced an augmented-reality component to its 3D mapping technology, overlaying street signs and other traffic infrastructure with identifying tags generated by its deep learning technology.
The system identifies objects and generates the tags to overlay on real-time video from a vehicle. The augmented-reality component is an addition to Civil Map’s localization platform, which builds maps of urban environments from and for self-driving cars.
With the Civil Maps model, a self-driving car compares what its sensors perceive of the outside world, including lane markings and signage, with an internal map, and correlates that reference with GPS coordinates. As the car compares its sensor data with its internal model, it can determine its position with a “relative accuracy of 10 centimeters.”