Analysis of Distracted Driver Behaviour Using Self-Organizing Maps

This work studies driving under different distractions and how they affect driver's behaviour. Driving patterns are studied by constructing Self Organizing Maps and training it on the data for multiple drivers. This results in a structure that maps each driver under a particular distraction to their behaviour. The map is then analyzed by labeling features from the datasets. These labels serve to examine different behaviour of each driver.