In this section, we'll discuss a recent paper called ChauffeurNet: Learning to Drive by Imitating the Best and Synthesizing the Worst (https://arxiv.org/abs/1812.03079). It was released in December 2018 by Waymo, one of the leaders in the field of AV. Let's look at some of the properties of the ChaffeurNet model:
- It is a combination of two interconnected networks. The first is a CNN called FeatureNet, which extracts features from the environment. These features are fed as inputs to a second, recurrent network called AgentRNN, which determines the driving policy.
- It uses imitation supervised learning in a similar way to the algorithms we described in the Imitation driving policy section. The training set is generated based on records of real-world driving episodes. ChauffeurNet can handle complex driving situations, such as lane changes...
