Deep Learning Based Autonomous Driving in Vehicular Networks

When kids, we may have dreamed of playing video games and watching movies on the trip with our parents, while letting the cars drive by themselves. This finally becomes practical with the autonomous driving, which relies on the vehicles to sense and learn the environment and determine the driving behavior without or with few human operations. This, however, is quite challenging due to the huge data perceived from complicated traffic environment to be analyzed in real-time and the limited computing power of vehicles. In this chapter, we provide a brief survey on the state-of-the-art autonomous driving technology. Towards this goal, we present the basic structure of hardware and software modules of autonomous vehicles and the application of deep learning in autonomous driving. In particular, note that by using wireless communications to connect vehicles as a network, the autonomous vehicles can share the information and collaboratively adjust the driving behaviors. We further propose a collaborative driving framework in which autonomous vehicles learn and drive with groups. Using simulations, we show how wireless communications can help with collaborative sensing and deep learning in autonomous driving.