I. Introduction
The research on advanced driver-assistance systems (ADASs) has gained increasing interest over the past decade. The incentive for this evolvement was the worldwide effort to reduce road accidents. The triggering effects for the blossoming of ADAS research were the technology advances that allowed cost-effective implementation of real-time image processing algorithms used in such systems. Nowadays, an increasing number of commercially available vehicles are equipped with lane detectors activating lane departure warnings, parking radars, collision warning sensors, etc. The goal of a completely autonomous commercially available vehicle has yet to be reached due to the vast diversity of driving environments and the unpredictability of incidents that could occur. When the available data used are limited to the visual information taken from onboard cameras, typical tasks such as road detection and collision avoidance become even more difficult. So far, only assistive systems have been implemented, a variety of which having been presented in [1] and [2].