Ambarella, a developer of low-power, HD and Ultra HD video processing semiconductors is demonstrating its fully autonomous EVA (Embedded Vehicle Autonomy) vehicle on Silicon Valley roads to industry analysts and customers.
EVA has been trained to deal with the various traffic scenarios presented by Silicon Valley’s challenging urban environment. The fully autonomous car combines software and algorithms based on over 20 years of autonomous vehicle research with Ambarella’s low-power CV1 embedded computer vision processors based on its CVflow architecture.
EVA’s high-resolution stereovision cameras deliver the 360-degree short and long distance viewing capability required for advanced perception and precise self-location. EVA includes sensor fusion of the vision information with Radar and map data to provide the information necessary for path planning and merging maneuvers without the need for additional LiDAR systems.
EVA’s CV1-based stereovision cameras provide a perception range of over 150 meters for stereo obstacle detection and over 180 meters for monocular classification. Stereovision processing enables detection of generic obstacles without training, allowing more robust decisions to be made.
EVA also uses stereovision to recognize visual landmarks and uses HD map information for high precision localization, even when the GPS signal is weak or not available, for example in dense urban locations. EVA features include automatic calibration, stereo generic obstacle detection, terrain modeling, traffic light detection, 3D free space detection, lane detection, curb and barrier detection, and CNN classification for vehicle, pedestrian, and bicycle/motorcycle.
Ambarella has also announced its next generation CV2 computer vision processor, which will provide up to 20 times the computer vision performance of CV1 in a fully-integrated SoC, delivering higher perception accuracy and further reducing the total number of chips required for a fully autonomous vehicle.