Driving behaviours are the root cause of millions of road accidents every year. Aggressive
and distracted driving are the two most important examples of driving misbehaviours. This …

Most road accidents occur due to human fatigue, inattention, or drowsiness. Recently,
machine learning technology has been successfully applied to identifying driving styles and …

Detection of driver aggressiveness is a significant method which helps to ensure safe
driving. Aggressive driving behavior is the cause every year of a vast number of traffic …

This research aims to develop a system that could classify aggressive driving maneuvers
with inexpensive sensors and smartphones via machine learning methods. Six aggressive …

Driving behavior classification is highly correlated with vehicle accidents and injury.
Automatically recognizing different driving behaviors is important for improving road safety …

Detection of dangerous driving behavior is a key component to improving road safety. It can
be successfully carried out using data collected by sensors widely available in smartphones …

Background: The lack of real-time monitoring is one of the reasons for the lack of awareness
among drivers of their dangerous driving behavior. This work aims to develop a driver …

The majority of traffic accidents are caused by human drowsiness, weariness and
absentmindedness. ML “Machine learning” technology has recently been used to accurately …

Road accidents are one of the most predominant factors for deaths throughout the world.
With the inclusion of several driver assistance systems, intelligent vehicles are becoming …

In this paper, a novel algorithm is proposed for monitoring driver behavior in the vehicle
cabin and evaluating the situations whether the driver operates a vehicle in a normal or …