Torc Robotics makes Amazon Web Services cloud provider for its self-driving truck fleet – Fleet Equipment Magazine

Torc Robotics has selected Amazon Web Services (AWS), Inc. as its preferred cloud provider to handle the scale and speed needed for data transfer, storage, and compute capacity as the company prepares to deploy its fleet of next-generation self-driving test trucks in New Mexico and Virginia. With the growth in test fleet size, number of routes, and sensor capability, Torc says there is an increase in data ingestion and analysis needs by engineering teams in the U.S. and in Germany.

Torc is an independent subsidiary of Daimler Truck AG, responsible for commercializing a Level 4 autonomous system that will be offered to trucking customers. As defined by the Society of Automotive Engineers (SAE), under Level 4 autonomy, a vehicle is capable of performing all driving functions under specified operating conditions.

Torc says AWS’s capabilities are designed to provide rapid, secure data transfer, intelligent tiered storage, managed orchestration and analytics tools, and high-performance multi-core CPU and GPU compute to help Torc rapidly scale its agile and cost-efficient development platform and accelerate its testing and commercialization of the technology.

Torc says its test fleet in New Mexico is already generating petabytes of data (1 petabyte is 1 million gigabytes) from tests on public roads.

Torc’s Level 4 self-driving vehicle system utilizes on-board computers that process sensor data in real time and host software that handles the dynamic driving tasks during autonomous runs, the company says. Torc will leverage AWS to increase the efficiency of data transfer from its on-road routes as their team continues to enhance the system.

Torc says its development team will utilize AWS for both low- and high-demand tasks, as well as data sharing across remote teams. This integration on AWS will allow Torc to transfer massive amounts of data for log analysis of real-world tests, while also providing computational power for simulation and deep learning, the company says.

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