Road course estimation in unknown, structured environments

The road course is an essential feature for many driver assistance systems and for autonomously-maneuvering vehicles. It is commonly stored in a map and hence assumed to be known a-priori. There are however situations in which the map data can become invalid, such as in road construction sites. In other situations, localization in the map might not be accurate enough, which can happen, for example, in dense urban areas. In this work, a novel approach to road course estimation is presented that is based on path planning through grid maps under non-holonomic and velocity constraints. With this approach, it is possible to estimate the road boundaries on a wide range of roads, including roads with continuous as well as discontinuous borders, roads exhibiting strong curvatures or S-shapes and road junctions. Furthermore, a plausibility measure is given to validate the road course and it is shown how the road center can be smoothed.