Imagine driving a car – one without self-driving capabilities – to a mall, airport or parking garage, then using an app to have the car drive off to park itself.
The system enables cars to move autonomously by directing their vehicle-to-everything, or so-called V2X, communication systems. These systems pass information from a vehicle to infrastructure, other vehicles, any surrounding entities – and vice versa. V2X technology, which comes standard in many modern cars, is used to improve road safety, traffic efficiency and energy savings.
LV5 CTRL TWR is built using Nvidia CUDA libraries for creating GPU-accelerated applications, as well as the Jetson AGX Orin module for high-performance AI at the edge. Nvidia GPUs are used in the cloud for global fleet path planning. Using V2X capabilities, LV5 CTRL TWR sends commands from infrastructure to cars, making vehicles turn right or left, move from point A to B, brake and more. It achieves an accuracy in positioning a car of plus or minus four centimetres.
“From the beginning, we knew we needed deep learning in the system in order to achieve the really high performance required to reach safety goals – and for that, we needed GPU acceleration,” Floor says. “So, we designed the system from the ground up based on Nvidia GPUs and CUDA.” “The compute capabilities of Jetson AGX Orin allow us to have the LV5 CTRL TWR cover more area with a single module,” Floor says. “Plus, it handles a wide temperature range, enabling our system to work in both indoor and outdoor units, rain or shine.”LV5 CTRL TWR is in early commercial deployment at a BMW manufacturing facility in Munich.