In order to drive by imitating an expert, we created a deep recurrent neural network (RNN) named ChauffeurNet that is trained to emit a driving trajectory by observing a mid-level representation of the scene as an input. A mid-level representation does not directly use raw sensor data, thereby factoring out the perception task, and allows us to combine real and simulated data for easier transfer learning