Stereo-based vision system for automotive imminent collision detection

Abstract

Imminent collision detection is an important functionality in the area of automotive safety. In the event that an unavoidable collision can be detected in advance of the actual impact, various measures can be taken to mitigate injury and damage. In this paper, we demonstrate that stereo vision is a promising solution to this problem. Our prototype system has been rigorously tested for different colliding scenarios (e.g., different intersection angles and different travelling speeds), including live tests in an industrial crash-test facility. We explain the novel algorithms behind the system, including an algorithm for detecting objects in depth images, and algorithms for estimating the travelling velocity of detected vehicles. Quantitative results and representative examples are also included.