Torc Robotics Recognized as a Finalist in PR Daily’s Social Media & Digital Awards

Torc Robotics Recognized as a Finalist in PR Daily’s Social Media & Digital Awards

Torc Takes Texas: Bringing Autonomous Trucking to Ft. Worth, Austin, and San Antonio

Torc Takes Texas: Bringing Autonomous Trucking to Ft. Worth, Austin, and San Antonio

If first responders and government officials can’t make it to Torc, Torc will bring autonomous trucking technology to them, especially in Texas!

Torc took to the Texas highways May 6 – 9, 2024, visiting locations in Ft. Worth, Austin, and San Antonio. With a traveling, custom-wrapped event trailer as our location on wheels and our ADS-ready Freightliner Cascadia, Torc hosted over two hundred first responders, transportation experts, and the public safety community. The week was filled with amazing conversations about autonomous trucking and Torc’s First Responder Interaction guides, while sharing Torc’s commitment to safety and innovation.

Torc’s First Responder Guide provides information on how first responders can safely interact with our trucks. More information about our First Responder Guide can be found here.

The tour was an important opportunity to share Torc’s vision and provide attendees with a first-hand experience with our innovative long-haul trucking technologies. Guests were able to climb into the truck cab, view the controls, and learn about the sensors, cameras, and software that encompass our autonomous driving system. Importantly, it provided education about the future ahead, answering questions, offering facts, and explaining how autonomy will help shape freight logistics.

Check out the video below for a recap of the event and more information from Michelle Chaka, Torc’s Senior VP of Safety and Regulatory.

In Case You Missed It:

Be sure and check out Michelle Chaka’s webinar on Safely Delivering Autonomous Trucking Solutions

 


Torc to Present Nine Papers at CVPR 2024

Torc to Present Nine Papers at CVPR 2024

Driving Autonomous AI with Torc’s Head of Intelligence

This summer, Torc’s Head of Artificial Intelligence, Felix Heide, and his team of both Princeton University and Torc colleagues will present an extraordinary total of nine papers at the IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR). Featuring information on geometry reconstruction, generative method, learning techniques, novel datasets and more, Felix and his team will exhibit their core competencies in researching and creating AI tools and techniques for self-driving artificial intelligence and beyond.

Torc at IEEE/CVF CVPR Conference

As one of the primary events in the field of computer vision, CVPR brings leading researchers, industry professionals, academics, and more, to a weeklong conversation about the latest findings in the world of computer vision and pattern recognition. With its main exhibition floor, presentations, and expert attendees, CVPR offers all levels of computer science professional with an opportunity to share their cutting-edge research and collaborate within the community. The IEEE/CVF CVPR Conference serves as the perfect backdrop for the innovative research Torc is spearheading.

The nine papers at CVPR 2024 cover a wide range of topics, each offering unique insights and contributions to the field. From advancements in neural rendering to new types of lidar, Felix, joined by his Princeton and Torc teams, has developed comprehensive content that reflects the depth and breadth of the industry’s expertise. Their work showcases the latest developments in computer vision and pattern recognition and indicates the ongoing progress of autonomous trucking technology.

Innovating Freight with AI

The significance of this research extends far beyond the confines of academic discourse. By pushing the boundaries of AI and machine learning, this work has the potential to revolutionize the autonomous driving industry and reshape the way we interact with technology. At Torc, these contributions help us pave the way for safer, more efficient freight systems that will benefit fleet professionals, everyday consumers, and all highway users.

As we move forward, AI research points us towards exciting new possibilities for collaboration and innovation. As academia, industry, and other research organizations come together to tackle the challenges of tomorrow, conferences like CVPR play a crucial role in fostering dialogue and driving progress. By sharing their insights and expertise, researchers like Felix and his team can shape the future of AI and propel us towards a world where driverless trucks enhance our lives in ways we’ve only begun to imagine.

These contributions not only highlight the cutting-edge research happening at Torc Robotics but also underscore the validity and potential of autonomous technology. As we continue to innovate our automated truck technology, our team’s contributions propel us to drive the future of freight in new and innovative ways. For our team, self-driving AI isn’t just a future concept, but a tangible reality that will make our world safer, faster, and stronger.

 

About Felix Heide, Torc’s Head of AI

Felix Heide is an industry leader in both artificial intelligence and autonomous technology. His journey to becoming an expert in general artificial intelligence, self-driving AI, and machine learning began long before his time at Torc, ranging from his first internship with NVIDIA Research in 2013 to his current role leading autonomous trucking development.

Felix is an Assistant Professor at Princeton University, Head of AI at Torc Robotics, and founder of the self-driving vehicle startup Algolux (now part of Torc). He is researching the theory and application of computational imaging and computer vision systems. Exploring imaging, vision, and display systems end-to-end, Felix’s work lies at the intersection of artificial intelligence, computer graphics, and computer vision.

He received his Ph.D. from the University of British Columbia, his undergraduate degree from the University of Siegen, and was a postdoc at Stanford University. His doctoral dissertation won the Alain Fournier Dissertation Award and the SIGGRAPH outstanding doctoral dissertation award. He won the NSF CAREER Award 2021 and the Sony Young Faculty Award 2021. He was named a Packard Fellow in 2022 and a Sloan Research Fellow in 2023. Felix was named SIGGRAPH New Significant Researcher in 2023.

 

 


This article is part one of three articles about Torc’s presence at CVPR this year. Look for more news about specific paper information, and the CVPR event in June.

Lane-Keeping in Self-Driving Trucks: Precision and Trust

Lane-Keeping in Self-Driving Trucks: Precision and Trust

Across all the features that self-driving technology has to offer, we might think of lane keeping as one of the most basic features possible. However, lane keeping is a complex behavior that relies on multiple components, sensors, and procedures to complete safe driving behaviors. In self-driving technology, precision is everything, making lane keeping a foundational necessity that underscores the safe and efficient operation of robotic trucks.

What is lane keeping?

Lane keeping is a critical driving functionality that ensures a vehicle stays within its designated lane on the road. Many newer consumer cars and commercial semi-trucks have some form of autonomous lane-keeping system programmed in, albeit there are several nuances and differences between types of lane-keeping systems, such as:

Lane Keep Assist (LKA)

Lane Keep Assist is a feature that can be toggled on and off on most vehicles. It typically works via camera, allowing the LKA to “see” the lane lines and nudge your vehicle within the lane lines when it begins to drift. However, because it’s camera-based, this feature may struggle to perform in muddy, snowy, or especially rainy conditions.

Lane Keep Assist is sometimes confused with Lane Departure Warning, which alerts drivers via haptic feedback, audible alerts, and sometimes indicator lights, if they’ve begun drifting out of the lane. Unlike other forms of lane-keeping systems, lane departure warning won’t correct the vehicle’s path. Instead, its job is to inform the driver that the vehicle is exiting the lane.

Lane Centering Assist (LCA)

Lane centering, sometimes called autosteer, takes LKA a step further. This feature is typically part of a vehicle’s adaptive cruise control, wherein a vehicle performs most highway behaviors itself while under human supervision. Lane centering is an active technology that keeps a vehicle in the center of its lane and can typically be turned on and off.

Today, many Class 8 trucks come equipped with various forms of Lane Keep Assist, Lane Centering Assist, and Adaptive Cruise Control. Aside from making drives safer for truck drivers and other highway users alike, these features can adjust throttle inputs and gear ratios for more efficient driving behaviors. By utilizing these features, drivers can optimize the amount of fuel their equipment consumes, reducing costs across the board.

Why is lane keeping important?

Lane keeping plays a foundational role in ensuring the safe and efficient operation of any vehicle, including our autonomous trucks. By enabling our robotic trucks to steadfastly maintain their designated lanes, we’re not only addressing a core competency in highway navigation but proving that our technology can be a safe foundation for a self-driving system.

Lane-keeping is important because of its impact on safety, but there are a few other reasons why we focus on this behavior as one of the most integral in safe-driving technology.

lane keeping

 

Traffic Flow and Predictability

When vehicles stay within their designated lanes, it reduces the likelihood of swerving and abrupt lane changes. When we humans learn to drive, we learn that being a predictable driver means being a safe driver.

Our autonomous technology is no different. In order to reduce the likelihood of traffic accidents and promote smoother traffic flow, we must ensure that other drivers are able to anticipate what our self-driving truck is going to do at all times. Whether that means keeping a consistent, steady pace within one lane or using an indicator light to shift lanes, predictability should be at the forefront of all lane-keeping behaviors.

Efficiency

By staying within the given lane, vehicles maximize the use of available road space, allowing more efficient traffic flow. During peak hours, when space is at a premium, this can reduce delays, avoid bottlenecks, and make it easier for vehicles to travel at a consistent speed throughout their journey.

How do self-driving cars and trucks stay in their lanes?

Self-driving trucks and self-driving cars stay in their lanes via cameras, Global Navigation Satellite Systems, LiDAR (or Light Detection and Ranging sensors), and more. Thanks to the work of autonomous driving engineers, our self-driving semi-trucks’ perception suite can recognize lane markers, interpret them correctly, and communicate this information to the rest of the system. From there, the autonomous driving system can utilize the information to maintain a set speed and keep watch on the distance between it and the vehicle in front of it.

There’s a common misconception that driverless cars and driverless trucks rely on lane markers alone to make sense of the path before them. While this used to be the case for very early self-driving cars, our autonomous abilities have advanced to grand new heights. Today, lane markers (and the cameras that “see” them) are just one piece of the puzzle.

Self-driving vehicles also utilize radar, which is sometimes found in Lane Keep Assist programs that we have in our day-to-day cars. Radar adds an additional safety component to lane navigation. Using radio waves to detect objects like other cars and traffic cones, radar helps paint the picture of what the driving environment looks like. In the same vein, mapping allows a self-driving vehicle to utilize historical information about the road to navigate in conjunction with the other tools in its toolbox. These two tools work with lane marker detection to assess the environment, calculate the safest possible behavior, and execute that behavior.

Lane Keeping and Robotic Trucks

As proponents of safe and sustainable self-driving practices, our autonomous driving system keeps in line with regulatory and industry best practices throughout all lane keeping behaviors. Aside from its impact on safety, proper lane keeping allows us to operate predictably to drivers on the road around us, prove our product’s viability, and promote a safe self-driving future.

As we forge ahead with our driverless trucking development, we will continue to innovate, collaborate, and lead the way in advancing our autonomous driving system. Through ongoing research, development, and collaboration with our stakeholders and partners, we will further enhance our lane-keeping capabilities to meet the evolving needs and expectations of the industry and the public. Together, we’re driving the future of freight.

 

 

Torc Robotics Wins 2024 Artificial Intelligence Excellence Award

Torc Robotics Wins 2024 Artificial Intelligence Excellence Award

Blacksburg, VA — March 21, 2024 — Torc Robotics announced today that it was named a winner in the Artificial Intelligence Excellence Awards program by The Business Intelligence Group.

As the world’s leading autonomous trucking solution, Torc delivers a focused, hub-to-hub autonomous truck product while providing customers with the safest, most reliable and cost-efficient solution on the market. Through its proprietary machine learning and AI technologies, Torc automates on-the-road data processing, enabling its software in a self-driving-18-wheeler-to take in data from its sensor suite and automatically classify it, helping the system define signs or objects made for human vision. In collaboration with carriers like C.R. England and Schneider on autonomous trucking pilots, and leveraging partnerships with Foretellix, Uber Freight, Aeva and others, Torc is driving its technology toward scalable commercialization in 2027.

“Artificial intelligence has allowed us to produce technology that was previously unimaginable on the road, and it’s an honor to be recognized for our efforts,” said Peter Vaughan Schmidt, CEO of Torc Robotics. “In order to reach our goal of commercialization of autonomous trucks by 2027, they must be safe, economically viable and produced and maintained at scale. With the help of AI, I’m proud to share that at Torc we’re working on all three.”

“We are truly honored to recognize Torc Robotics with this prestigious award,” stated Maria Jimenez, Chief Nominations Officer for the Business Intelligence Group. “The unwavering commitment of their team to excellence and their innovative AI applications have catapulted them to this remarkable achievement. Congratulations to the entire organization!”


 

About Torc Robotics

Torc Robotics, headquartered in Blacksburg, Virginia, is an independent subsidiary of Daimler Truck AG, a global leader and pioneer in trucking. Founded in 2005 at the birth of the self-driving vehicle revolution, Torc has over 18 years of experience in pioneering safety-critical, self-driving applications. Torc offers a complete self-driving vehicle software and integration solution and is currently focusing on commercializing autonomous trucks for long-haul applications in the U.S. Torc operates test facilities in Albuquerque, New Mexico, and engineering offices in Austin, Texas; Stuttgart, Germany; and Montreal, Canada. Torc’s purpose is driving the future of freight with autonomous technology. As the world’s leading autonomous trucking solution, we empower exceptional employees, deliver a focused, hub-to-hub autonomous truck product, and provide our customers with the safest, most reliable, and cost-efficient solution to the market.

About Business Intelligence Group 
The Business Intelligence Group was founded with the mission of recognizing true talent and superior performance in the business world. Unlike other industry award programs, these programs are judged by business executives having experience and knowledge. The organization’s proprietary and unique scoring system selectively measures performance across multiple business domains and then rewards those companies whose achievements stand above those of their peers.

 

Contact
Laura Lawton
press@torc.ai

Maria Jimenez
+1 909-529-2737
jmaria@bintelligence.com

New Talent, Technology and Partners: Daimler Truck and Torc Enter Fifth Year of Collaboration With Eyes on the Future

New Talent, Technology and Partners: Daimler Truck and Torc Enter Fifth Year of Collaboration With Eyes on the Future

(Blacksburg, Va./Stuttgart, Germany – January 16, 2023) – As Torc Robotics and Daimler Truck AG enter their fifth year of partnership, the companies are focused on bringing top talent into the organization and building and innovating through industry collaboration and partnerships. The goal of the collaboration is to commercialize Level 4 autonomous trucks for long-haul applications closer to a reality in the U.S.

“Over the past four years, we have seen the results of our strong collaboration with Daimler Truck and look forward to continuing to build upon the momentum and successes to bring us closer to the clear path of commercialization and safe deployment of autonomous trucks for long-haul applications,” said Peter Vaughan Schmidt, Torc Robotics CEO.

Joanna Buttler, Head of Global Autonomous Technology Group at Daimler Truck, adds: “Working with Torc, we have always managed to combine our ideas for the right solutions. The result is a fully integrated state-of-the-art autonomous truck that can safely handle highly complex traffic situations. In this spirit of authoring the future, we are looking forward to bringing SAE Level 4 autonomous trucks for hub-to-hub operations to the US market by 2027 together.”

Milestones

Team Growth

Over the past year, Torc has brought on some of the brightest innovators in the autonomous technology space with the goal of continuing to build out a dynamic leadership team that positions Torc and Daimler as leaders in autonomous driving system development, innovation, and fleet testing.

King joins as Chief Engineering Officer

In May, C.J. King joined the Torc leadership team as chief engineering officer. King, who was previously vice president of software engineering at HERE Technologies, brings more than 18 years of engineering, software, hardware, and autonomous expertise to the company. His leadership is driving the unification of all Torc’s engineering efforts to align with the company’s roadmap and key milestones. King’s experience on a global scale also supports Torc’s engineering team in its preparations for the commercial launch of Torc’s autonomous truck solution. King has extensive expertise in product development, managing global, diverse teams, technology optimizations, and new-system implementations as a result of his previous roles at HERE Technologies, Amazon, Ford, and Toyota.

Michelle Chaka joins as Senior Vice President, Safety and Regulatory

In February, Michelle Chaka joined Torc as senior vice president, safety and regulatory, bringing more than 25 years of safety and regulatory expertise to the company. Chaka serves as the safety champion for Torc, fostering a culture that values safety, data-driven and evidence-based approaches, and transparency. Chaka has experience leading automated driving research projects sponsored by the National Highway Traffic Safety (NHTSA) from which NHTSA published the learnings to all stakeholders. In her 25 years in the industry, Chaka has a unique mix of experience from her work at General Motors, Ford Motor Company, Virginia Tech Transportation Institute, and most recently, Locomation.

Scanlon joins as Vice President of Product Management

In August, Sheila Scanlon joined Torc as the new vice president of product management. Scanlon brings over 20 years of experience in the technology and autonomous driving industry to the Torc team. In her role, she works alongside Torc leadership to foster a customer-centric culture and data-driven mindset, leading the product planning and prioritization activities in alignment with engineering. Scanlon’s experience covers a broad range of applications across the autonomous driving space, including leadership roles at Aptiv, HERE Technologies, Mercedes Benz, and RRAI.

Capabilities and Technology

Torc acquires leader in computer vision and machine learning

In an effort to strengthen core competencies required for commercialization of Level 4 autonomous trucking, Torc acquired Algolux, a leader in computer vision and machine learning, in February 2022. The acquisition brought together Algolux’s end-to-end artificial intelligence (AI) stack, along with Torc’s groundbreaking autonomous-driving technology. Robust perception technology is key to helping Torc’s autonomous system correctly identify objects during difficult visual conditions such as low light, fog or bad weather. Algolux’s software is currently running on autonomous ready Freightliner Cascadia test vehicles.

Partnerships and Collaboration

Torc and C.R. England join forces on long-haul autonomous trucking pilots

Early this year, Torc announced a strategic collaboration with C.R. England, one of North America’s premier transportation companies. The partnership allows Torc to implement a pilot program leveraging C.R. England’s temperature-controlled loads and Torc’s fleet of Level 4 autonomous test trucks for long-haul applications. The collaboration is Torc’s first expansion into refrigerated freight. The pilot will provide select customers with temperature-controlled capacity and world-class service, while giving unique insights to help guide the development and ongoing commercialization of autonomous trucks for long-haul applications.

Dutch organization joins Torc for scenario-based safety validation

In late 2022, Torc announced a partnership with the Netherlands Organization for Applied Scientific Research (TNO) that would allow Torc and TNO to work together to substantiate the safety of self-driving trucks using scenario-based safety validation. TNO’s StreetWise, a safety validation methodology based on a real-world scenario database, provides a large collection of “driving events” designed to test and validate autonomous driving systems’ performance according to the latest safety requirements. The resulting scenario information enables Torc to apply thorough, virtual validation, according to state-of-the-art international safety assessment processes.

For more information on Torc, please visit www.torc.ai.


About Torc Robotics
Torc Robotics, headquartered in Blacksburg, Virginia, is an independent subsidiary of Daimler Truck AG, a global leader and pioneer in trucking. Founded in 2005 at the birth of the self-driving vehicle revolution, Torc has over 18 years of experience in pioneering safety-critical, self-driving applications. Torc offers a complete self-driving vehicle software and integration solution and is currently focusing on commercializing autonomous trucks for long-haul applications in the U.S. Torc operates test facilities in Albuquerque, New Mexico, and engineering offices in Austin, Texas; Stuttgart, Germany; and Montreal, Canada. Torc’s purpose is driving the future of freight with autonomous technology. As the world’s leading autonomous trucking solution, we empower exceptional employees, deliver a focused, hub-to-hub autonomous truck product, and provide our customers with the safest, most reliable, and cost-efficient solution to the market.

About Daimler Truck
Daimler Truck is the pioneer of truck automation. In 2014, the world’s leading truck manufacturer presented the Mercedes-Benz Future Truck 2025, the world’s first automated truck, and was the first to demonstrate the technological opportunities and great potential that automated trucks offer customers and society. In 2015, Daimler’s Freightliner Inspiration Truck obtained the first-ever road license for a partially automated commercial vehicle demonstrating the promise of automated driving on the highways of Nevada. Today, Daimler Truck offers partially automated driving features (SAE Level 2) with the Mercedes-Benz Actros, the Freightliner Cascadia and the FUSO Super Great.

Daimler Truck North America has developed the autonomous-ready Freightliner Cascadia – the foundation of a smart autonomous driving system. The Class 8 truck is equipped with redundant functions that enable the deployment of autonomous trucking and are ideal for the integration of autonomous software, hardware, and compute. Designed and developed with a second set of critical systems, such as steering and braking, the vehicle meets Daimler Truck’s uncompromising safety standards. As part of the Autonomous Technology Group, DTNA is also researching the infrastructure required for the operational testing of initial application cases. DTNA is contributing to the successful development of autonomous driving technology and vehicle integration for heavy-duty trucks.

Media Contacts
Torc: Laura Lawton
Daimler Truck: Paul Mandaiker
Daimler Truck North America: Anja Weinert