[Machine Learning/AI] Path Planning and Lane Selection Research - [Machine Learning/AI] Path Planning and Lane Selection Research - HRI-US
[Machine Learning/AI] Path Planning and Lane Selection Research
Highway is an essential road type in urban transportation systems and one of the major areas where fatal accidents occur. Motion planning under high speed traffic hence requires multi-directional perceptions and prediction of other drivers, as well as a timely decision making, and needs to be formulated as a multi-objective problem.
You are expected to:
- Implement state-of-the-art long horizon lane selection algorithms (for lane choice and/or gap choice).
- Research and develop a long horizon lane selection algorithm while considering risk, drive comfort, and travel time.
- M.S. or Ph.D. candidate computer science, or related STEM field.
- Strong familiarity and research experience in deep learning, optimizations, and control of robotic systems.
- Highly proficient in software engineering using C++ and/or Python.
- Experience with deep learning software like TensorFlow or PyTorch.
- Familiarity with ROS.
- Hands-on experience with robotic control.
Duration: 3 months