… , micro servers, autonomous vehicles and home gateways are … our survey and the existing
surveys on federated learning. … First, we classify the federated learning approaches based on …

… existing random methods. The HydRand used in this article is different from other existing
methods in … improve the ability of driverless vehicle to recognize vehicles and pedestrians. In …

… For example, we can use the model averaging approach in the Federated Averaging (FedAvg)
algorithm proposed by Google [19], where the gradient parameters of local models are …

… Through an ITS case study, the ability of a federated model … When considering possible
methods of advanced … When considering a system of fully autonomous vehicles, image …

… deep learning approaches for cyber security in the Internet of … Then, we review the
vulnerabilities in federated learning-… IoT, including, autonomous vehicles, driver assistance, …

… In this article, we give an overview of a new approach, known as federated learning, which
is a possible solution for these challenges. We survey existing works on federated learning, …

… approach, federated learning (FL) is a natural solution for massive user-owned devices in
edge computing with distributed and private training data. FL methods … autonomous vehicles to …

… We study federated learning in VEC to meet the rapidgrowing demands of AI applications
in … In this paper, we study federated learning in VEC, which is important for generalizing AI …

… sensors in autonomous vehicles to … This learning process proposed by the FL approach
has proven its effectiveness and efficiency in several case studies, in particular, in our case study …

… using federatedlearning has become more and more important in vehicular networks due to
the anticipated growth of connected autonomous vehicles with … The review of this article was …