CS27 BAC+5 - Stage Decision-making for lane changing maneuvers under uncertainty in automated driving systems (H/F)
Core
Develop algorithms for safe and efficient lane changing maneuvers in automated driving systems under uncertain traffic conditions.
Role type
Research intern (final year Master's) in automated driving decision-making
Builds
Intelligent decision-making algorithms for lane changing in dynamic environments
Domain
Automotive / Autonomous Driving / AI
Deliverable
production ML models
Required skills
vehicle motion planning, control theory, algorithm design, simulation, Python, C++, optimization
Preferred skills
reinforcement learning, sequential decision-making, automotive simulators
Responsibilities
Review state-of-the-art lane changing methods, design theoretical representations of highway scenarios, implement decision-making algorithms in simulation, test scenarios with uncertain factors, analyze performance regarding safety/efficiency/comfort, document results
Seniority
Intern (final year Master's student)