The application of naturalistic driving data (NDD) has the potential to answer critical
research questions in the area of driving behavior assessment, as well as the impact of …

The rate of advancement in autonomous systems has been increasing and humans rely on
such systems for every aspect of daily life. This is especially true in the area of autonomous …

The digitalisation of geriatric care refers to the use of emerging technologies to manage and
provide person-centered care to the elderly by collecting patients' data electronically and …

Distracted driver activity recognition plays a critical role in risk aversion-particularly
beneficial in intelligent transportation systems. However, most existing methods make use of …

Integrating driver, in-cabin, and outside environ-ment's contextual cues into the vehicle's
decision making is the centerpiece of semi-automated vehicle safety. Multiple systems have …

There is extensive evidence that mobile phone use while driving contributes significantly to
driver distraction, increasing the risk of traffic accidents. This work proposes a method to …

Road detection plays a vital role in automated driving and advanced driver assistance
systems. In recent years, mainstream frameworks have suffered from the restrictions of a …

In recent years, traffic forecasting has gradually attracted attention in data mining because of
the increasing availability of large‐scale traffic data. However, it faces substantial challenges …

Graph neural networks (GNNs) have recently grown in popularity in the field of artificial
intelligence (AI) due to their unique ability to ingest relatively unstructured data types as …

In recent years, detection techniques using computer vision and deep learning have shown
promise in assessing driver distraction. This paper proposes a fusion network that combines …