System Helps Humans Predict When Self-Driving Cars Will Make Mistakes
The CW-Net technique explains the behavior of an autonomous vehicle using understandable concepts. “Instead of just wondering why the car stopped, having real-time data provides feedback that lets you test the system during deployment,” says AI researcher Eoin Kenny.
Self-driving cars are often controlled by deep learning models that sometimes fail in unexpected situations. For instance, the car might inexplicably brake and block the path of an oncoming emergency vehicle.