Blockchain-FRL for Vehicular Lane Changing: Toward Traffic, Data, and Training Safety-Reference-Cited by-同舟云学术

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Blockchain-FRL for Vehicular Lane Changing: Toward Traffic, Data, and Training Safety

Published:2023-12-15 Issue:24 Volume:10 Page:22153-22164
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Fan Bo¹^ORCID,Dong Yiwei¹^ORCID,Li Tongfei¹^ORCID,Wu Yuan²^ORCID

Affiliation:

1. Beijing Key Laboratory of Traffic Engineering, College of Metropolitan Transportation, Beijing University of Technology, Beijing, China

2. Department of Computer and Information Science, State Key Laboratory of Internet of Things for Smart City, University of Macau, Macau, China

Funder

NSFC

Fund for the Development of Sciences and Technology

Basic and Applied Basic Research Foundation of Guangdong Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/6488907/10353047/10215343.pdf?arnumber=10215343

Reference42 articles.

1. Connected automated vehicle cooperative control with a deep reinforcement learning approach in a mixed traffic environment

2. RLSS: A Reinforcement Learning Scheme for HD Map Data Source Selection in Vehicular NDN

3. Digital Twin Empowered Mobile Edge Computing for Intelligent Vehicular Lane-Changing

4. Fairness-Aware Federated Learning With Unreliable Links in Resource-Constrained Internet of Things

5. A Stackelberg Game and Federated Learning Assisted Spectrum Sharing Framework for IoV

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