Mercedes-Benz Funds Educational Initiatives in AI, Automated Driving at Universities

Mercedes-Benz’s strategic funding for Stanford School of Engineering will enable 15 graduate students to conduct hands-on research in AI and its application in the automotive industry

UC San Diego’s 3D imaging research allows Mercedes-Benz R&D North America (MBRDNA) to tap into the institutional research resources at the Autonomous Vehicle Laboratory.

Stanford students will have the chance to explore artificial intelligence technology integration while working on the NTG-7 hyperscreen test bench. Image courtesy of Business Wire.a

Mercedes-Benz Research & Development North America, Inc. (MBRDNA), a Silicon Valley-headquartered research and development subsidiary of Mercedes-Benz, has started new research collaborations with two universities: Stanford University School of Engineering and the University of California San Diego’s Contextual Robotics Institute. MBRDNA has earmarked a 6-month funding initiative aimed at advancing the research of artificial intelligence and its potential to elevate in-car passenger experience and autonomous driving.

New Research Horizons for Stanford Students

Stanford, recognized as one of the “cradles of AI innovation” since the establishment of the Stanford Artificial Intelligence Lab (SAIL) in the 1950s, has been chosen by MBRDNA as a key enabler in advancing the AI-driven passenger experience. Fifteen Stanford students enrolled in Course Project-Based Design, Innovation and Development will have the opportunity to embark on field trips to two global hubs of innovation at Mercedes-Benz: MBRDNA’s headquarters in Silicon Valley, CA; and Mercedes-Benz’s global headquarters in Stuttgart, Germany.

The academic challenge presented to the students is related to the MBUX Virtual Assistant, for which Mercedes-Benz has used advanced software and generative AI to create an even more natural relationship with the car. Divided into three teams, Stanford students are formulating project ideas, exploring the full spectrum of possibilities with AI, from optimizing the productivity of customers’ daily commutes to addressing the challenging task of parking, and refining a personalized in-car voice assistant powered by fine-tuned large language models.

“Mercedes-Benz’s educational collaborations with Stanford and UCSD are more than a financial funding commitment; they underscore our dedication to fostering the next generation of leaders in the tech space. We look forward to the discoveries and advancements that will emerge from our collaboration,” says Philipp Skogstad, president and CEO at Mercedes-Benz Research & Development North America

“We’re grateful to MBRDNA for their support that provides students with experiential learning opportunities, particularly as they relate to the possibilities that AI enables in the automotive sector,” says Jay Borenstein, lecturer for Stanford’s Project-Based Design, Innovation and Development course.

3D Imaging Research at UC San Diego

Strengthening MBRDNA’s commitment to academic institutions is the newly expanded research scope with the Contextual Robotics Institute at the University of California San Diego Jacobs School of Engineering. Led by Institute Director and UC San Diego Computer Science Professor Henrik I. Christensen, the research team’s Autonomous Vehicle Laboratory (AVL) focuses on perception and fusion for automated driving, particularly on 3D scene reconstruction from camera images, which could contribute to the safety features of V systems. The objective of this project is to initiate an effort building on prior work from Christensen’s lab and integrate it with a real-time 4D Neural Radiance Fields (NERFs) model to build a model segmented into semantically meaningful regions.

“We are very excited to join forces with Mercedes Benz Research North America to expand our work on dynamic scene models for autonomous driving,” says Professor Hendrik I. Christensen. “This is a great opportunity for us to broaden our approach and also build a new alliance.”

Sources: Press materials received from the company and additional information gleaned from the company’s website.

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