Vehicular Networks and Autonomous Driving Cars

In this chapter, we discuss the role of federated learning for vehicular networks. Due to the high mobility of autonomous cars, there might not be seamless connectivity of the end-devices within cars with the roadside units, and thus traditional federated learning might not work well. To overcome this challenge, we introduced a dispersed federated learning framework for autonomous driving cars. We formulate a dispersed federated learning cost optimization problem and proposed an iterative scheme. Finally, we present extensive simulation results to validate the proposal.