An efficient and reliable asynchronous federated learning scheme for smart public transportation
Since the traffic conditions change over time, machine learning models that predict traffic
flows must be updated continuously and efficiently in smart public transportation. Federated …
flows must be updated continuously and efficiently in smart public transportation. Federated …
An incentive mechanism of incorporating supervision game for federated learning in autonomous driving
Federated learning (FL), as a distributed machine learning technology, allows large-scale
nodes to utilize local datasets for model training and sharing without revealing privacy …
nodes to utilize local datasets for model training and sharing without revealing privacy …
Joint air-ground distributed federated learning for intelligent transportation systems
Supported by some of the major revolutionary technologies, such as Internet of Vehicles
(IoVs), Edge Computing, and Machine Learning (ML), the traditional Vehicular Networks …
(IoVs), Edge Computing, and Machine Learning (ML), the traditional Vehicular Networks …
Semi-synchronous federated learning protocol with dynamic aggregation in internet of vehicles
In an Internet of Vehicle (IoV) system, federated learning (FL) is a new approach to process
real-time vehicle data in a distributed way, which can improve the driving experience and …
real-time vehicle data in a distributed way, which can improve the driving experience and …
A survey on federated learning in intelligent transportation systems
The development of Intelligent Transportation System (ITS) has brought about
comprehensive urban traffic information that not only provides convenience to urban …
comprehensive urban traffic information that not only provides convenience to urban …
A survey of federated learning for connected and automated vehicles
Connected and Automated Vehicles (CAVs) represent a rapidly growing technology in the
automotive domain sector, offering promising solutions to address challenges such as traffic …
automotive domain sector, offering promising solutions to address challenges such as traffic …
DRL-based adaptive sharding for blockchain-based federated learning
Blockchain-based Federated Learning (FL) technology enables vehicles to make smart
decisions, improving vehicular services and enhancing the driving experience through a …
decisions, improving vehicular services and enhancing the driving experience through a …
Privacy-preserving blockchain-based federated learning for traffic flow prediction
Y Qi, MS Hossain, J Nie, X Li - Future Generation Computer Systems, 2021 - Elsevier
As accurate and timely traffic flow information is extremely important for traffic management,
traffic flow prediction has become a vital component of intelligent transportation systems …
traffic flow prediction has become a vital component of intelligent transportation systems …
Federated learning in intelligent transportation systems: Recent applications and open problems
Intelligent transportation systems (ITSs) have been fueled by the rapid development of
communication technologies, sensor technologies, and the Internet of Things (IoT) …
communication technologies, sensor technologies, and the Internet of Things (IoT) …
Federated learning for connected and automated vehicles: A survey of existing approaches and challenges
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 …
(CAV), including perception, planning, and control. However, its reliance on vehicular data …