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.
Vehicular Networks and Autonomous Driving Cars
Wireless Networks
2021-08-09
42 pages
Article/Chapter (Book)
Electronic Resource
English
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