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Research Intern: Interaction-Aware Behavior Planning for Autonomous Driving Systems
Job Number: P25INT-26
Honda Research Institute USA (HRI-US) is seeking a talented and motivated PhD-level research intern to explore interaction-aware behavior planning for autonomous driving. The intern will design and evaluate high-level decision-making frameworks that enable autonomous vehicles to reason about surrounding agents and select appropriate maneuvers, which can then be passed to downstream path and motion planners. Emphasis will be placed on developing safe, interpretable, and adaptive decision-making strategies that generalize to complex, dynamic multi-agent traffic environments.
Mountain View, CA
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Key Responsibilities
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- Conduct a survey of interaction-aware planning methods, such as rule-based and learning-enhanced approaches, including imitation learning and reinforcement learning.
- Design and implement a hierarchical behavior planner that outputs maneuver-level goals and constraints for downstream planning stacks.
- Define formal interfaces for intended behaviors (goals, corridors, safety constraints) to enable modular integration.
- Integrate the developed planner into a simulation framework (e.g., ROS 2 with CARLA) and evaluate across diverse driving scenarios.
- Collaborate closely with HRI scientists to refine algorithms and support experimental deployment.
- Contribute to publications targeting top conferences such as ICRA, or CoRL.
Minimum Qualifications
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- Ph.D. candidate in Robotics, Computer Science, Mechanical Engineering, or similar fields.
- Strong background and experience in at least one of the followings: Motion Planning and Decision-Making under Uncertainty, Interaction-Aware Planning, Active Learning, Reinforcement Learning and Imitation learning.
- Familiarity with simulation environments and planning frameworks for autonomous driving.
- Programming and software design skills in C++ or Python.
- Self-motivated and able to conduct independent research and prototyping.
Bonus Qualifications
- Research experience in Robotics/Automated vehicles Motion Planning and Control, Machine learning.
- Prior published research on hybrid control, multi-agent interaction handling, behavior modeling
- Experience integrating learning models into control/planning pipelines (e.g., learned cost functions, behavior cloning policies)..
- Strong software development experience.
- Experience with using ROS-framework packages.
- Experience using public datasets and simulators for navigation research
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| Years of Work Experience Required |
0 |
| Desired Start Date |
5/11/2026 |
| Internship Duration |
3 Months |
| Position Keywords |
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Learning-enhanced planning, hybrid learning-control systems,
multi-agent interaction, autonomous driving
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Alternate Way to Apply
Send an e-mail to careers@honda-ri.com with the following:
- Subject line including the job number(s) you are applying for
- Recent CV
- A cover letter highlighting relevant background (Optional)
Please, do not contact our office to inquiry about your application status.
