Fusion of clothoid segments for a more accurate and updated prediction of the road geometry

Abstract

basic step in the development of advanced driver assistance systems is the perception and interpretation of information on the vehicle environment. In many cases, the upcoming road geometry in front the own vehicle is of particular interest. Although a prediction of the course of the road can be provided based on map data, the accuracy is not sufficient for most driver assistance systems. The goal of this work is to achieve a more accurate and updated prediction of the road geometry at close range. Therefore, the map data is combined with the information from an existing vision-based lane detection system. Since the shape of detected road lines as well as the map data are represented by clothoid curves, the emphasis of this work is placed on the calculation, combination, and connection of clothoid segments.