In this document, I would like to share some personal notes about the latest exciting trends in research about decision making for autonomous driving. I keep on updating it 👷 🚧 😃
"title"
[ Year
]
[📝 (paper)]
[ (code)]
[🎞️ (video)]
[ 🎓 University X
]
[ 🚗 company Y
]
[ related
, concepts
]
- Architecture and Map
- Behavioural Cloning, End-To-End and Imitation Learning
- Inverse Reinforcement Learning, Inverse Optimal Control and Game Theory
- Prediction and Manoeuvre Recognition
- Rule-based Decision Making
- Model-Free Reinforcement Learning
- Model-Based Reinforcement Learning
- Planning and Monte Carlo Tree Search
Besides, I reference additional publications in some parallel works:
- Hierarchical Decision-Making for Autonomous Driving
- Educational application of Hidden Markov Model to Autonomous Driving
- My 10 takeaways from the 2019 Intelligent Vehicle Symposium
Looking forward your reading suggestions!
2020-10-12 [
refactor
- split categories into separate files, sincegithub
can not show files larger than1MB
].