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Federated Learning for Connected and Automated Vehicles: A Survey of Existing Approaches and Challenges
Citations:
54
References:
243
Abstract
Machine learning (ML) is widely used for key tasks in Connected and Automated Vehicles (CAV), including perception, planning, and control. However, its reliance on vehicular data for model training presents significant challenges related to in-vehicle user privacy and communication overhead generated by massive data volumes. Federated learning (FL) is a decentralized ML approach that enables multi...
Keywords
2023
Article
Open Access
2-Y Citation Average
8.077
Language
Country
Federated Learning for Connected and Automated Vehicles: A Survey of Existing Approaches and Challenges
Citations:
54
References:
243
Abstract
Machine learning (ML) is widely used for key tasks in Connected and Automated Vehicles (CAV), including perception, planning, and control. However, its reliance on vehicular data for model training presents significant challenges related to in-vehicle user privacy and communication overhead generated by massive data volumes. Federated learning (FL) is a decentralized ML approach that enables multi...
Keywords
2023
Article
Open Access
2-Y Citation Average
8.077
Language
Country