Abstract: The present invention describes a road terrain detection system that comprises a method for classifying selected locations in the environment of a vehicle based on sensory input signals such as pixel values of a camera image. The method comprises a high level spatial feature generation for selected locations in the environment called base points. The spatial feature generation of the base points is based on a value-continuous confidence representation that captures visual and physical properties of the environment, generated by so called base classifiers operating on raw sensory data. Consequently, the road terrain detection incorporates both local properties of sensor data and their spatial relationship in a two-step feature extraction process.

Abstract: The invention relates to a system and method for lane relative position estimation. The environment of a vehicle is first sensed, and spatial features are then extracted and classified from information obtained from the sensing. The spatial features capture lateral position information within a lane, and an output signal including the result of the classification, which represents the relative lateral positioning of a road location with respect to the overall lane shape, is generated.

Abstract: The invention relates to a system and method for lane relative position estimation, wherein first the environment of a vehicle is sensed with at least one sensor means; then spatial features from information obtained from the sensor means are extracted which are then classified. The spatial features capture lateral position information within a lane and an output signal including the result of the classification which represents the relative lateral positioning of a road location with respect to the overall lane shape is generated.

Abstract: The present invention describes a road terrain detection system that comprises a method for classifying selected locations in the environment of a vehicle based on sensory input signals such as pixel values of a camera image. The method comprises a high level spatial feature generation for selected locations in the environment called base points. The spatial feature generation of the base points is based on a value-continuous confidence representation that captures visual and physical properties of the environment, generated by so called base classifiers operating on raw sensory data. Consequently, the road terrain detection incorporates both local properties of sensor data and their spatial relationship in a two-step feature extraction process.