This is quite an interesting field that I want to get into. Combination of AI, software and robotics. Also see Autonomous Racing.
I am breaking into this field through my school’s self-driving car design team: WATonomous.
- Self-Driving Cars seminar by Lex Friedman (2019)
- Lex Friedman, Companies in the self driving space (2018)
- L5kit looks neat
- Other random repos:
- Waymo Open Dataset
Learned a lot of this listening to George Hotz.
Challenges of Self-Driving Car
Some of the challenges of building self-driving cars (from Cruise talk)
- Low Latency
- Correct (avoid system level false-negatives)
1: Static world, solved by mapping 2: Dynamic world, where there are cars around 3: These cars around are reacting to you, potentially solved by reinforcement learning
The self-driving car problem can be divided into 3 components:
- Planning (Cars)
- Prediction (Self-Driving Cars)
The levels of Self-Driving Car
The Society of Automotive Engineers (SAE) defines 6 levels of driving automation ranging from 0 (fully manual) to 5 (fully autonomous). These levels have been adopted by the U.S. Department of Transportation.
Big companies are moving to combine Perception and Planning into end-to-end control, see Modular vs. End-to-End