A Forward Collision Avoidance System Adopting Multi-feature Vehicle Detection

Abstract

This paper presents a vehicle collision avoidance method and it is associated with the exploitation of multiple features based on the AdaBoost classifier result. The proposed system will enhance the precision rate and accuracy of vehicle detection from 72% to 96% using an AdaBoost detection method extracting multiple features in vehicle detection and false alarms are reduced.