Products on Show
DAY 2: Open-architecture solution for rapid prototyping and AD development
Klas has announced at the expo that its RAVEN (Ruggedized Autonomous Vehicle Network) open-architecture solution for rapid prototyping and development of ADS and ADAS now supports logging from GMSL2 cameras.
The company is showcasing the capabilities of RAVEN’s TRX D8 datalogger, which boasts write speeds of up to 7Gb per second and a storage capacity of 240TB, which Elektrobit claims make it the fastest datalogger on the market for its compact size.
All systems are integrated to accelerate development. The modular solution eliminates the need to build cumbersome test rigs and source equipment from multiple vendors, saving time and cost. Developers can connect ruggedized components back-to-back, eradicating complex cabling and potential failure points. Its modules include 10GbE interfaces that are interconnected by a high-performance network switch with a 121Gbps backplane, removing network bottlenecks.
RAVEN’s open and flexible architecture enables multiple AV developers to easily create, build and run autonomous driving stacks in-vehicle, saving costs and test vehicle setup times.
Its high-performance compute supports Nvidia GPUs, allowing developers to train vision detection algorithms live during test drives, thereby reducing engineering cycles and time. SerDes logging captures GMSL2 camera data with minimal intrusion on the data transmission, ensuring vehicles can continue to operate safely. Native automotive Ethernet support makes it easier to connect to the next generation of sensors and ECUs, maximizing return on investment through reusability in future use cases.
RAVEN supports a virtualization layer, allowing multiple test stacks to be run simultaneously. No additional hardware is needed while new systems are being designed, eliminating weeks of procurement effort and downtime waiting on vehicle hardware delivery. It also supports a 40Gbps networking trunk, maximizing throughput from the development platform to external networks, resulting in faster access to real-world data.
“The ability to intelligently harvest data at the automotive edge is key to delivering safe, driverless experiences,” explained Frank Murray, CTO of Klas. “With RAVEN, not only can driving stacks be developed faster, but by leveraging its compute, real-world evaluations can be done in a closed system, ensuring test vehicles and other road users remain safe as the software evolves.”