CW-Net translates self-driving car reasoning into human-understandable concepts
Researchers introduced CW-Net, a method that translates the reasoning process of an autonomous vehicle’s AI into understandable concepts that explain its behavior. The approach is intended to help humans predict when self-driving cars might make mistakes.