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 **Warning:**You do not have the permission to access the upload fields on this form. Contact the form owner or portal administrator to request the access.