Human Interactive Driving Intern - Safe Shared Control
About The Position
At Toyota Research Institute (TRI), we're on a mission to improve the quality of human life. We're developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we've built a world-class team in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavior Models, and Robotics. This is a Summer 2026 paid 12-week internship opportunity. Please note that this internship will be a hybrid in-office role. The Team Within the Extreme Performance Intelligent Control team, we are developing techniques to advance vehicle safety and performance capabilities using tools from machine learning, optimization, and control theory. We are pursuing a cooperative approach to high-performance driving by developing predictive models and control frameworks for extreme vehicle maneuvering that match or exceed the skills of expert drivers. We envision a world where these tools allow each vehicle to support its driver, creating a safe and enjoyable experience for all. The Internship We are seeking a motivated intern to join our shared control driving team, focusing on cutting-edge research to ensure safe and effective human-AI collaboration for the next generation of advanced driver assistance systems. Potential research areas include developing novel planning and control algorithms to guarantee safety amid challenging driving scenarios, improving performance of existing shared control algorithms under uncertain conditions, and implementing data-driven/ML approaches to shared control with safety guarantees. This role provides an exciting opportunity to explore approaches to human-AI pairing that support safe, intuitive, and responsive shared driving systems. Along the way, you will apply your knowledge to tackle novel research questions and work towards a publication with professional researchers. The internship will be in our headquarters and includes competitive compensation, befitting the challenging but fun nature of the research work at TRI. Applicants with relevant publications in the fields above and good collaboration skills are highly encouraged to apply.
Requirements
- Ph.D. or M.S. student in relevant fields - ML/AI, robotics, computer science, mechanical engineering, aerospace engineering, or similar.
- Proficient in scientific Python, robotic frameworks (e.g. ROS2.0). Proficiency in machine learning frameworks (e.g. PyTorch) are a plus.
- Knowledge of nonlinear system control, optimization, and machine learning.
- Experience working on joint scientific and engineering projects.
Nice To Haves
- Vehicle dynamics knowledge is a plus.
- Familiarity with or interest in racing or high-performance driving is a plus.
Responsibilities
- Work with researchers to develop and then undertake a well-scoped research project in a relevant area.
- Extend existing controls/AI/ML algorithms or design new algorithms for shared control with a human driver at a vehicle's performance limits.
- Explore approaches to formalize guarantees of safety for shared control algorithms.
- Implement algorithms on a full-scale vehicle research platform.
- Publish your original research at a high-impact conference.
Benefits
- TRI offers a generous benefits package including vacation and sick time.
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What This Job Offers
Career Level
Intern
Industry
Professional, Scientific, and Technical Services
Number of Employees
101-250 employees
