Abstract: A method and an apparatus for the evaluation of detection results of components for road detection, of the road estimated by a road estimation, and/or of the planned trajectory of the driver assistance systems of an ego-transportation vehicle, wherein the detection results, the estimated road, and the planned trajectory are designated a hypothesis. To evaluate the components, the road estimation, or the driver assistance system, use is made of a metric based on the manually covered trajectory of the ego-transportation vehicle, wherein the deviation between the manually traveled trajectory and the hypothesis is determined for predefined reference points at a predefined interval from a starting point in a transportation vehicle-based x-y coordinate system and by using the evaluation, it is determined whether the hypothesis of the components for road detection, the road estimation, and/or the driver assistance system fulfill predefined criteria.

Abstract: A method and an apparatus for the evaluation of detection results of components for road detection, of the road estimated by a road estimation, and/or of the planned trajectory of the driver assistance systems of an ego-transportation vehicle, wherein the detection results, the estimated road, and the planned trajectory are designated a hypothesis. To evaluate the components, the road estimation, or the driver assistance system, use is made of a metric based on the manually covered trajectory of the ego-transportation vehicle, wherein the deviation between the manually traveled trajectory and the hypothesis is determined for predefined reference points at a predefined interval from a starting point in a transportation vehicle-based x-y coordinate system and by using the evaluation, it is determined whether the hypothesis of the components for road detection, the road estimation, and/or the driver assistance system fulfill predefined criteria.

Abstract: The present invention relates to a method for determining arrangement information for a vehicle (10). The arrangement information comprises a position of the vehicle (10) and an orientation of the vehicle (10) with respect to a stationary coordinate system. In the method, a local driving lane arrangement in the surroundings of the vehicle (10) is detected with sensors (14) of the vehicle (10). A first driving lane arrangement is determined with respect to the stationary coordinate system in dependence on the local driving lane arrangement and a previously determined arrangement information item for the vehicle. A second driving lane arrangement is determined with respect to the stationary coordinate system in dependence on predefined map material.

Abstract: The present invention relates to a method for determining arrangement information for a vehicle (10). The arrangement information comprises a position of the vehicle (10) and an orientation of the vehicle (10) with respect to a stationary coordinate system. In the method, a local driving lane arrangement in the surroundings of the vehicle (10) is detected with sensors (14) of the vehicle (10). A first driving lane arrangement is determined with respect to the stationary coordinate system in dependence on the local driving lane arrangement and a previously determined arrangement information item for the vehicle. A second driving lane arrangement is determined with respect to the stationary coordinate system in dependence on predefined map material.

Abstract: An in-vehicle system for estimating a lane boundary based on raised pavement markers that mark the boundary. The in-vehicle system includes a camera for obtaining image data regarding reflective raised pavement markers and non-reflective raised pavement markers, an image processor for processing frames of image data captured by the camera, a lidar detector for obtaining lidar data regarding reflective raised pavement markers, and a lidar processor for processing frames of lidar data captured by the lidar detector. The image processor generates a first probabilistic model for the lane boundary and the lidar processor generates a second probabilistic model for the lane boundary. The in-vehicle system fuses the first probabilistic model and the second probabilistic model to generate a fused probabilistic model and estimates the lane boundary based on the fused probabilistic model.

Abstract: An in-vehicle system for estimating a lane boundary based on raised pavement markers that mark the boundary. The in-vehicle system includes a camera for obtaining image data regarding reflective raised pavement markers and non-reflective raised pavement markers, an image processor for processing frames of image data captured by the camera, a lidar detector for obtaining lidar data regarding reflective raised pavement markers, and a lidar processor for processing frames of lidar data captured by the lidar detector. The image processor generates a first probabilistic model for the lane boundary and the lidar processor generates a second probabilistic model for the lane boundary. The in-vehicle system fuses the first probabilistic model and the second probabilistic model to generate a fused probabilistic model and estimates the lane boundary based on the fused probabilistic model.