Intelligent transportation systems (ITSs) have been fueled by the rapid development of
communication technologies, sensor technologies, and the Internet of Things (IoT) …

Federated learning (FL) is a collaborative, decentralized privacy‐preserving method to
attach the challenges of storing data and data privacy. Artificial intelligence, machine …

Nowadays mobile positioning devices, such as global navigation satellite systems (GNSS)
but also external sensor technology like cameras allow an efficient online collection of …

The growing number of cars on city roads has led to an increase in traffic accidents,
highlighting the need for traffic safety measures. Mobile trajectory anomaly detection is an …

Predictive maintenance has emerged as a critical application in modern transportation,
leveraging sensor data to forecast potential damages proactively using machine learning …

Federated learning (FL) has the potential to mitigate privacy risks and communication costs
associated with classical machine learning and data science approaches. Given the …

With the development of modern technology, the application of various types of devices in
life has become more extensive, especially with the emergence of the Internet of Things …

Federated learning is a decentralized approach used to train global machine learning
models without sharing data between participants, and it has become a key solution present …

Connected vehicles provide communication and data collection from vehicles, which
enables new technology to enhance system based on usage data. In this paper, we present …