Vision-based vehicle detection and inter-vehicle distance estimation

In this paper, we propose a vision-based robust vehicle detection and inter-vehicle distance estimation algorithm for driving assistance system. It uses the directional edge features, as well as the Haar-like features of car rear-shadows for detection of front vehicles. The use of additional vehicle edge features greatly reduces the false-positive errors. And, after analyzing two inter-vehicle distance estimation methods: the vehicle position-based and the vehicle width-based algorithm, a novel improved inter-vehicle distance estimation algorithm that uses the advantage of both methods is proposed. Various experimental results show the effectiveness of the proposed method.