Learning Robust Driving Policies

Learning Robust Driving Policies

Andreas Geiger via YouTube Direct link

Evaluation

21 of 25

21 of 25

Evaluation

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Classroom Contents

Learning Robust Driving Policies

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  1. 1 Intro
  2. 2 Conditional Imitation Learning
  3. 3 Sunny, light traffic
  4. 4 Sunny, heavy traffic
  5. 5 Rain, heavy traffic
  6. 6 Sunset, heavy traffic
  7. 7 Inspiration: World Models
  8. 8 Learning Situational Driving
  9. 9 Importance of Mixture Model and Task-based Refinement
  10. 10 Emergent Driving Modes
  11. 11 Results on CARLA Benchmark
  12. 12 Results on CARLA NoCrash Benchmark
  13. 13 Results on AnyWeather Benchmark
  14. 14 CILRS: Collision, infraction
  15. 15 LSD: No collision, proper braking
  16. 16 Formal Definition of Imitation Learning General Imitation Learning
  17. 17 Challenges of Behavior Cloning
  18. 18 Experiment by Held and Hein
  19. 19 Distribution over Driving Actions
  20. 20 Dagger with Critical States and Replay Buffer
  21. 21 Evaluation
  22. 22 Infractions Analysis
  23. 23 Training Variance
  24. 24 Qualitative Results
  25. 25 Summary

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