Ambarella introduces CV22AQ automotive camera SoC for ADAS
Ambarella, Inc. introduced the CV22AQ automotive camera system-on-chip (SoC), featuring the Ambarella CVflow computer vision architecture for deep neural network (DNN) processing. Target applications include front advanced driver-assistance systems (ADAS) cameras, electronic mirrors with blind spot detection (BSD), interior driver and cabin monitoring cameras, and around view monitors (AVM) with parking assist. The company says that the new SoC provides the performance necessary to exceed New Car Assessment Program (NCAP) requirements for applications such as lane keeping, automatic emergency braking (AEB), intelligent headlight control, and speed assistance functions. Fabricated in advanced 10 nm process technology, its low power consumption reportedly supports the small form factor and thermal requirements of windshield-mounted forward ADAS cameras.
"To date, front ADAS cameras have been performance-constrained due to power consumption limits inherent in the form factor," said Fermi Wang, CEO of Ambarella. "CV22AQ provides an industry-leading combination of outstanding neural network performance and very low typical power consumption of below 2.5 watts. This breakthrough in power and performance, coupled with best-in-class image processing, allows tier-1 and OEM customers to greatly increase the performance and accuracy of ADAS algorithms."
The CV22AQ's CVflow architecture provides computer vision processing in 8 MP resolution at 30 frames per second to enable object recognition over long distances and with high accuracy. CV22AQ supports multiple image sensor inputs for multi-FOV (Field of View) cameras and can also create multiple digital FOVs using a single high-resolution image sensor to reduce system cost. It enables DNNs for object detection, classification (i.e., of pedestrians, vehicles, traffic signs, and traffic lights), tracking, as well as high-resolution semantic segmentation for applications such as free space detection.
The CV22AQ's high-performance image signal processor (ISP) provides imaging in low-light conditions, while high dynamic range (HDR) processing extracts maximum image detail in high-contrast scenes. It includes efficient 8 MP encoding in both AVC and HEVC video formats, allowing customers to add video recording and streaming capabilities to their automotive cameras. The SoC's cybersecurity features, which include secure boot, TrustZone, and I/O virtualization, enable over-the-air updates (OTA) and also protect against hacking.
A complete set of tools is provided to help customers port their own neural networks onto the CV22AQ SoC. The toolkit includes a compiler, debugger, and support for industry-standard machine learning frameworks such as Caffe and TensorFlow, with extensive guidelines for DNN performance optimizations.
CV22AQ is currently sampling to leading Tier 1 customers and Tier 2 algorithm providers. Chip samples with ASIL-B support are targeted to be available in 2019.
CV22AQ SoC key features include AEC-Q100 grade 2, high-speed SLVS/MIPI/LVCMOS interfaces,
quad-core 756 MHz ARM Cortex A53 with NEON DSP extensions and FPU, multi-channel ISP with up to 576 MP/s input pixel rate, and multi-exposure HDR processing and LED flicker mitigation. A set of interfaces includes gigabit Ethernet, USB 2.0 host and device, dual SD card controllers with SDXC support, HDMI v2.0, and MIPI DSI/CSI-2 4-lane output.
CV22AQ will be demonstrated in a variety of applications during CES 2019.