In this chapter, we explored the applications of deep learning in AVs. We started with a brief historical overview of AV research and we discussed the different levels of autonomy. Then we described the components of the AV system and identified when it's appropriate to use DL techniques. Next, we looked at 3D-data processing and PointNet. Then we introduced the topic of implementing driving policies using behavioral cloning, and we implemented an imitation learning example with PyTorch. Finally, we looked at Waymo's ChauffeurNet system.
This chapter concludes our book. I hope you enjoyed the read!