Federated vehicular transformers and their federations: Privacy-preserving computing and cooperation for autonomous driving

Y Tian, J Wang, Y Wang, C Zhao… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Cooperative computing is promising to enhance the performance and safety of autonomous
vehicles benefiting from the increase in the amount, diversity as well as scope of data …

Multi-sensor Fusion and Cooperative Perception for Autonomous Driving: A Review

C Xiang, C Feng, X Xie, B Shi, H Lu… - IEEE Intelligent …, 2023 - ieeexplore.ieee.org
Autonomous driving (AD), including single-vehicle intelligent AD and vehicle–infrastructure
cooperative AD, has become a current research hot spot in academia and industry, and …

Federated learning for green and sustainable 6G IIoT applications

VK Quy, DC Nguyen, D Van Anh, NM Quy - Internet of Things, 2024 - Elsevier
The 6th generation mobile network (6G) is expected to be launched in the early 2030s. The
architecture of 6G will be the convergence of space, air, ground, and undersea networks …

V2X cooperative perception for autonomous driving: Recent advances and challenges

T Huang, J Liu, X Zhou, DC Nguyen… - arXiv preprint arXiv …, 2023 - arxiv.org
Accurate perception is essential for advancing autonomous driving and addressing safety
challenges in modern transportation systems. Despite significant advancements in computer …

[HTML][HTML] FL-MAAE: An Intrusion Detection Method for the Internet of Vehicles Based on Federated Learning and Memory-Augmented Autoencoder

L Xing, K Wang, H Wu, H Ma, X Zhang - Electronics, 2023 - mdpi.com
The Internet of Vehicles (IoV) is a network system that enables wireless communication and
information exchange between vehicles and other traffic participants. Intrusion detection …

[HTML][HTML] Intrusion detection method for internet of vehicles based on parallel analysis of spatio-temporal features

L Xing, K Wang, H Wu, H Ma, X Zhang - Sensors, 2023 - mdpi.com
The problems with network security that the Internet of Vehicles (IoV) faces are becoming
more noticeable as it continues to evolve. Deep learning-based intrusion detection …

Deep reinforcement learning based vehicle selection for asynchronous federated learning enabled vehicular edge computing

Q Wu, S Wang, P Fan, Q Fan - International Congress on Communications …, 2023 - Springer
In the traditional vehicular network, computing tasks generated by the vehicles are usually
uploaded to the cloud for processing. However, since task offloading toward the cloud will …

Federated Learning in Intelligent Transportation Systems: Recent Applications and Open Problems

S Zhang, J Li, L Shi, M Ding, DC Nguyen… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Intelligent transportation systems (ITSs) have been fueled by the rapid development of
communication technologies, sensor technologies, and the Internet of Things (IoT) …

Optimization of edge server group collaboration architecture strategy in IoT smart cities application

F Gou, J Wu - Peer-to-Peer Networking and Applications, 2024 - Springer
With the development of big data and communication technologies, the Internet of Things
(IoT) has permeated all aspects of smart cities. IoT smart city application scenarios are …

[HTML][HTML] DAG-based swarm learning: a secure asynchronous learning framework for Internet of Vehicles

X Huang, H Yin, Q Chen, Y Zeng, J Yao - Digital Communications and …, 2023 - Elsevier
To provide diversified services in the intelligent transportation systems, smart vehicles will
generate unprecedented amounts of data every day. Due to data security and user privacy …