The Need of Advanced Driver-Assistance System’s Development based on an Analysis of Road Accidents

Abstract

aking a look at the numbers of road accidents using Machine Learning techniques and configuring predictions based on historic data, the paper aims to emphasize the need of a method to decrease numbers of accidents. Machine learning techniques have shown great potential in analyzing large-scale datasets related to road accidents. By leveraging these techniques, researchers have been able to identify key contributing factors, such as driver behavior, road conditions, and vehicle characteristics, which play a crucial role in accident occurrence. Through the analysis of historical accident data, machine learning models can effectively predict the likelihood of future accidents and identify high-risk areas, enabling proactive measures to be implemented. ADAS systems provide real-time information and assist drivers in making informed decisions while driving, thereby mitigating potential risks. A particular interest of this Article is underlining the importance of ADAS in the automotive field and how it can benefit the drivers.

Keywords

• machine learning
• adas
• road accidents
• automotive industry