Public-road testing in Michigan marks the next step in Torc’s growth, technology development and path to commercialization.
Torc Robotics
BLACKSBURG, Va. -- Torc, a self-driving subsidiary of Daimler Truck AG, has expanded autonomous truck testing operations to public roads in Michigan, deploying the latest-generation Daimler Truck autonomous chassis based on the Freightliner Cascadia, a Class 8 long-haul truck. The move builds on Torc's previous testing in Dallas-Fort Worth and Blacksburg.
Testing its autonomous trucks in the Ann Arbor, Michigan, area represents Torc's next step in bringing this technology safely and reliably to the long-haul trucking industry. After establishing an engineering office in Ann Arbor last year, the development work is now on the road and contributing to Torc’s next generation of software. This enables the validation of autonomous performance across new environments and seasonal conditions for both hardware and software using real-world data.
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“Validating our hardware and software together on public roads is a critical step in the marathon toward autonomous trucking commercialization,” said Felix Heide, Head of Artificial Intelligence at Torc. “Each new hardware generation allows us to further validate our AI inference models, strengthen our simulation accuracy, and ensure our autonomous system performs safely and reliably in real-world conditions.”
According to McKinsey & Company, the autonomous heavy-duty trucking market could reach $616 billion in 2035, with China (about $327 billion), the U.S. (about $178 billion), and Europe (about $112 billion) accounting for the bulk.
The Michigan testing expansion builds on Torc’s continued partnership with the Michigan Economic Development Corporation (MEDC), the Michigan Department of Transportation (MDOT) and Ann Arbor SPARK, reflecting a shared commitment to advancing safety and innovation in the freight industry through autonomous trucking.
Torc is currently hiring in Michigan and remotely for software engineering, artificial intelligence, and machine learning roles to support ongoing testing and development efforts.
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