Aquantia, Bosch, Continental, NVIDIA, and Volkswagen announced the formation of the Networking for Autonomous Vehicles (NAV) Alliance to drive the ecosystem development required for the next generation of multi-gig ethernet networking in vehicles.
“Redundant and diverse AI algorithms are the key to level 5 automation. However, the volume of data generated by multiple types of sensors (camera, radar, lidar, and ultrasound) can reach 32 TB every 8 hours—that level of data transfer calls for a new breed of ultra-high-speed networks, including multi-gig ethernet. The NAV alliance will catalyze the development of a reliable next generation of networking platform for self-driving cars,” said James Hodgson, Senior Analyst Autonomous Driving, ABI Research.
This next-generation networking architecture is based on an array of ECUs, CPUs, GPUs, high-definition cameras, sensors, gateways, and storage devices, all connected through a high-speed, multi-gigabit/s ethernet network that works to seamlessly move data throughout the vehicle securely and reliably.
NAV Alliance’s founding objectives are to
- Promote development of new specifications, as well as build consensus for new technologies related to multi-gig ethernet automotive networking
- Create procedures and testing requirements to endeavor to ensure interoperability, security, and reliability of the in-vehicle network
- Promote products and solutions that adhere to the new specifications
- Liaise with standards bodies to build consensus, create IEEE proposals, and promote standardization
- Build awareness and educate the marketplace and users on the requirements for autonomous vehicle networks
Founding members will focus on these core objectives and expand the NAV Alliance membership roster in the coming months to include additional automotive suppliers and manufacturers.
Gary Hicok, Senior Vice President of Hardware Development, NVIDIA, said, “Autonomous vehicles require an onboard AI supercomputer, architected for functional safety, capable of processing vast amounts of sensor data through redundant and diverse deep neural networks and algorithms. Multi-gig ethernet has a proven track record for interoperability and scalability, making it a natural choice for automotive connectivity, delivering critical data from the sensor suite to the vehicle’s AI brain.”