Driver distraction behavior recognition is currently a significant study area that involves
analyzing and identifying various movements, actions, and patterns exhibited by drivers …

Deep learning has been widely utilized in intelligent vehicle systems, particularly in the field
of driver distraction detection. However, existing methods in this application tend to focus …

Vehicle crash rates caused by distracted driving have been rising in recent years. Hence,
safety while driving on roads is today a crucial concern across the world. Some of the …

Human drivers have different driving styles, experiences, and emotions due to unique
driving characteristics, exhibiting their own driving behaviors and habits. Various research …

The increasing number of car accidents is a significant issue in current transportation
systems. According to the World Health Organization (WHO), road accidents are the eighth …

We propose a multi-task learning framework for improving the performance of vision-based
deep-learning approaches for driver distraction recognition. The most popular tool so far for …

Recognition of driving distraction using driver’s motion and deep learning Page 1
Proceedings of the 2020 IISE Annual Conference L. Cromarty, R. Shirwaiker, P. Wang, eds …

As the proportion of road accidents increases each year, driver distraction continues to be
an important risk component in road traffic injuries and deaths. The distractions caused by …

Driver behavior recognition is crucial for traffic safety in intelligent transportation systems. To
understand the driver distraction behavior, deep learning methods has been used to learn …

Driver distraction is a principal cause of traffic accidents. In a study conducted by the
National Highway Traffic Safety Administration, engaging in activities such as interacting …