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, since github can not show files larger than 1MB].