1 Introduction
2 Deep Learning Based Decision-Making Architectures for Self-Driving Cars
3 Overview of Deep Learning Technologies
3.1 Deep Convolutional Neural Networks
3.2 Recurrent Neural Networks
3.3 Deep Reinforcement Learning
4 Deep Learning for Driving Scene Perception and Localization
4.1 Sensing Hardware: Camera vs. LiDAR Debate
4.2 Driving Scene Understanding
4.3 Perception Using Occupancy Maps
5 Deep Learning for Path Planning and Behavior Arbitration
6 Motion Controllers for AI-Based Self-Driving Cars
6.1 Learning Controllers
6.2 End-to-End Learning Control
7 Safety of Deep Learning in Autonomous Driving
8 Data Sources for Training Autonomous Driving Systems
9 Computational Hardware and Deployment
10 Discussion and Conclusions
10.1 Final Notes