Research Intern: Semantic-Aware Interaction and Behavior Planning for Autonomous Driving

Honda Research Institute USA; Mountain View (CA); On-site; USD 34,000 - 52,000; Full time

Job summary

Honda Research Institute USA in Mountain View invites a research intern to advance semantic-aware interaction and behavior planning for autonomous driving. You will explore scene context and agent intent to inform high-level decisions and integrate with the real-time navigation stack.

The role emphasizes independent research, collaboration with HRI researchers, and evaluating methods in simulation and real-world datasets, with opportunity to contribute to publications and demonstrations.

Qualifications

• Ph.D. candidate in Robotics, CS, EE, or ME.
• Strong background in behavior planning and motion planning.
• Experience in robotics or autonomous systems algorithms.
• Proficient in Python and/or C++.
• Familiar with ML frameworks PyTorch or TensorFlow.
• Ability to conduct independent research.

Responsibilities

• Conduct research on semantic-aware behavior planning and interaction-aware decision making for autonomous driving.
• Develop methods using scene context, agent intent, and semantic relationships.
• Investigate representations like semantic features and interaction graphs.
• Develop decision-making strategies for interactions such as yielding and rerouting.
• Integrate methods with existing navigation and motion-planning algorithms.
• Train and evaluate methods using simulation and real-world datasets.
• Evaluate algorithm-level performance and impact on closed-loop behavior.
• Collaborate with researchers and contribute to publications and demonstrations.

Skills

Behavior planning

Motion planning

Decision making

Autonomous driving

Reinforcement learning

Multi-agent systems

Python

C++

Education

Ph.D. candidate in Robotics/CS/EE/ME

Tools

PyTorch

TensorFlow

ROS/ROS2

Job description

Research Intern: Semantic-Aware Interaction and Behavior Planning for Autonomous Driving - Honda Research Institute USA

Research Intern: Semantic-Aware Interaction and Behavior Planning for Autonomous Driving

Job Number: P25INT-56

Honda Research Institute USA (HRI-US) is seeking a research intern to develop semantic-aware interaction and behavior planning methods for autonomous driving. The intern will investigate how scene context, agent intent, interaction information, and semantic relationships can be used to make higher-level driving decisions such as when to proceed, yield, wait, reroute, or adapt to other road users. The developed methods will integrate with HRI’s existing real-time navigation and motion-planning stack and will be evaluated in challenging low-speed autonomous-driving and parking scenarios.

Mountain View, CA

Key Responsibilities

• Conduct research on semantic-aware behavior planning and interaction-aware decision making for autonomous driving.
• Develop methods that use scene context, agent intent, interaction relationships, and uncertainty to make high-level driving decisions.
• Investigate representations such as semantic features, scene/interaction graphs, multi-hypothesis agent behaviors, or learned behavior models.
• Develop decision-making strategies for interactions such as yielding, passing order, waiting, rerouting, and conflict resolution.
• Integrate developed methods with existing HRI navigation and motion-planning algorithms.
• Train and evaluate methods using simulation and real-world driving datasets.
• Evaluate both algorithm-level performance and impact on closed-loop autonomous-driving behavior.
• Collaborate with HRI researchers and contribute toward technical publications and system demonstrations.

Minimum Qualifications

• Ph.D. candidate in Robotics, Computer Science, Electrical Engineering, Mechanical Engineering, or a related field.
• Strong background in at least one of the following: behavior planning, motion planning, decision making, reinforcement learning, autonomous driving, or multi-agent systems.
• Experience developing and evaluating algorithms for robotics or autonomous systems.
• Programming proficiency in Python and/or C++.
• Familiarity with machine learning frameworks such as PyTorch or TensorFlow.
• Ability to conduct independent research and prototype solutions.

Bonus Qualifications

• Experience with interaction-aware planning, behavior planning, or decision making for autonomous vehicles or mobile robots.
• Experience with numerical optimization and optimization-based planning, including familiarity with QP/NLP solvers or tools such as IPOPT, CasADi, or similar.
• Familiarity with intent prediction, trajectory prediction, semantic reasoning, or scene understanding.
• Experience with methods such as reinforcement learning, graph-based representations, or uncertainty-aware planning.
• Experience integrating learning-based or decision-making algorithms with downstream motion planners.
• Experience with ROS/ROS2 and autonomous-driving or robotics simulation environments.
• Experience working with real-world autonomous-driving datasets and closed-loop evaluation.
• Experience implementing algorithms on a real robotic or autonomous vehicle platform is a plus.
• Prior research publications in robotics, autonomous driving, machine learning, or related areas are a plus.

Years of Work Experience Required 0

Desired Start Date 1/11/2027

Internship Duration 3 Months

Position Keywords Autonomous Driving,Robotics,Behavior and Motion Planning