The Toyota Research Institute (TRI) has expanded its research into applying AI to driving with the addition of a further 13 universities to its collaborative research programme. The 13 universities, all based in the United States, join current Toyota collaborators MIT, Stanford and the University of Michigan. The new additions will collaborate in the next five year phase of TRI’s research programme.

The next phase of the research programme will comprise 35 joint research projects focused on technological challenges in research into automated driving, robotics and machine assisted cognition (MAC). 

The next five-year phase will include the investment of more than $75 million in the academic institutions, making it one of the largest collaborative research programmes by an automotive company in the world.

“Our first five-year programme pushed the boundaries of exploratory research across multiple fields, generating 69 patent applications and nearly 650 papers,” said Eric Krotkov, TRI Chief Science Officer who leads the university research program. “Our next five years are about pushing even further and doing so with a broader, more diverse set of stakeholders.  To get to the best ideas, collaboration is critical.  Our aim is to build a pipeline of new ideas from different perspectives and underrepresented voices that share our vision of using AI for human amplification and societal good.”   

The universities taking part in the next phase of TRI’s collaborative programme are: 

• Carnegie Mellon University
• Columbia University
• Florida A&M University-Florida State University College of Engineering
• Georgia Institute of Technology (Georgia Tech)
• Indiana University
• Massachusetts Institute Technology (MIT)
• Princeton University
• Smith College
• Stanford University
• Toyota Technological Institute at Chicago (TTIC)
• University of California, Berkeley
• University of Illinois
• University of Michigan
• University of Minnesota
• University of Pennsylvania
• UCLA

The first phase of the programme, conducted over the last five years, sponsored 98 projects involving about 100 faculty members and over 200 students. These projects yielded technology advances for ongoing TRI projects, including transfer learning in computer vision, self-supervised learning on contact-rich tasks, and techniques for mimicking human behavior in various driving interactions. 

The first phase projects generated several awards for published papers at leading conferences including the CVPR 2018 Best Paper, an ICRA 2019 Finalist Best Paper, the ICRA 2019 Best Paper, and the 2020 IEEE Robotics and Automation Letters Best Paper Award. Additionally, the close collaborations resulted in the recruitment of several new TRI team members.

This next five-year phase focuses investments in projects TRI researchers have a keen academic interest in exploring to create more value and impact for TRI. Each project features a TRI researcher as a co-investigator who will work with the university partner. This approach directly engages TRI researchers with the academic AI partners and ensures that the research contributes to the TRI mission.

TRI is also offering Young Faculty Researcher (YFR) projects to form partnerships with more junior (typically pre-tenure) faculty members. Whereas joint projects have TRI pursuing a specific direction and reaching technical milestones along the way, the YFR projects are specifically designed to support promising tenure stream faculty members, enabling them to explore broadly, inquire deeply, and address higher-risk, higher-payoff ideas. In YFR projects, TRI invests in the researcher and provides them with the freedom and flexibility to pivot from one direction to another.