Abstract: Vehicle-based motorcycle lane-splitting assist system dynamically detects lane-splitting motorcycles using rearward facing radar sensors installed in the vehicle. The system detects moving objects approaching the vehicle from the rear using the radar sensor data. The velocity of a fast-moving object is compared to other detected objects and observed over a number of radar cycles to confirm that the object can be classified as a lane-splitting motorcycle. Once the classification is made, the system causes a visual and/or audible warning, that a motorcycle is lane-splitting and approaching the vehicle, to be issued to the driver of the vehicle.

Abstract: The disclosure relates to a method and an assistance apparatus for supporting vehicle functions in a parking lot. Surroundings data are recorded and processed in order to recognize semantic and/or geometric objects, wherein the surroundings data depict the parking lot or represent same in the form of a point cloud. Data portions are extracted from the surroundings data, these data portions corresponding to semantic and/or geometric objects that have been classified as relevant to a parking maneuver and comprising pixels or data points that depict or represent the recognized semantic and/or geometric objects. Of the surroundings data, only the extracted data portions together with object data that, as a semantic and/or geometric attribution of the data portions, in each case indicate to which at least one semantic and/or geometric object the data portions correspond, are then sent to a server in order to automatically create an overall map.

Abstract: A method for detecting at least one intersection point of road marking lines, wherein a computing unit of a transportation vehicle receives a camera image and identifies a first road marking line based on the camera image. Using the computing unit, a search region is automatically defined in an environment of the first road marking line, and an automatic search limited to the search region is performed. At least one intersection point of the first road marking line with at least a second road marking line is identified as the result of the search.

Abstract: A device for detecting the surroundings of a vehicle and a method for detecting the surroundings, and a vehicle designed to carry out said method comprise a camera module, a camera control apparatus, an analysis unit and an illumination device. The illumination device is formed by a matrix headlight of the vehicle and is designed such that it can project a light pattern into the surroundings. The projected light pattern is imaged in the detection region of the camera module and the 3D position of measurement points formed by the light pattern in the surroundings is determined by the analysis unit. However, the illumination device projects the light pattern only into regions of the surroundings in which the analysis unit has ascertained, based on image data, a value that is critical for 3D position determination.

Abstract: Technologies and techniques for providing a traffic lane localization for a motor vehicle in a region of an infrastructure device and to the motor vehicle. An infrastructure message is received, including at least one portion of traffic lane count information that describes a number of traffic lanes in the region of the infrastructure device. A portion of environment information is provided, which describes an environment of the motor vehicle in the region of the infrastructure device. A portion of adjacent traffic lane information is determined, which describes a number and relative arrangement of adjacent traffic lanes by evaluating the provided environment information. A portion of traffic lane localization information is determined, which describes how the ego traffic lane is localized relative to the adjacent traffic lane by evaluating the received infrastructure message and the determined adjacent traffic lane information. The determined traffic lane localization information is then provided.

Abstract: Disclosed is a method for determining the position of a vehicle, in which highly accurate localization data for positions of the vehicle are determined when traveling along a route. Odometric measured variables for the own odometry of the vehicle are captured when traveling along the route. The highly accurate localization data determined and the odometric measured variables captured are jointly evaluated. The own odometry of the vehicle is corrected on the basis of the evaluation. An error model is used to calculate a vehicle-specific drift for the own odometry of the vehicle and to continually correct the own odometry of the vehicle provided highly accurate localization data can be determined. The corrected own odometry of the vehicle can then be used in areas in which highly accurate localization data cannot be determined in order to determine the position of the vehicle.

Abstract: The disclosure relates to a method and to a server apparatus and to a motor vehicle for automatically mapping a surrounding area. In the method, the server apparatus creates a route network map of the surrounding area from odometry data from a fleet of respective motor vehicles. The server apparatus generates a mapping plan for mapping sections of the surrounding area. The mapping plan divides the surrounding area into multiple subareas and defines at least one subarea that is still to be mapped. The fleet vehicles are then iteratively instructed to collect surroundings data in accordance with the mapping plan only for subareas that are still to be mapped and to transmit said surroundings data to the server apparatus, and the mapping plan is accordingly updated based on the received surroundings data in order to avoid collecting and transmitting redundant surroundings data for subareas that have already been mapped.

Abstract: Systems and methods of evaluating parking spaces are provided, and in particular evaluating parking spaces in parking lots or parking garages, with regard to autonomous driving. This is accomplished by determining an accessible area of the parking space, and defining grid points in the accessible area. Features of the parking space are determined for each of the grid points, where each of the features is registrable from a respective one of the grid points. A quality value is obtained from an average number of features that is registrable from each of the grid points.

Abstract: The disclosure relates to a method and an assistance apparatus for supporting vehicle functions in a parking lot. Surroundings data are recorded and processed in order to recognize semantic and/or geometric objects, wherein the surroundings data depict the parking lot or represent same in the form of a point cloud. Data portions are extracted from the surroundings data, these data portions corresponding to semantic and/or geometric objects that have been classified as relevant to a parking maneuver and comprising pixels or data points that depict or represent the recognized semantic and/or geometric objects. Of the surroundings data, only the extracted data portions together with object data that, as a semantic and/or geometric attribution of the data portions, in each case indicate to which at least one semantic and/or geometric object the data portions correspond, are then sent to a server in order to automatically create an overall map.

Abstract: According to a method for self-localization of a vehicle, a first pose of the vehicle is determined in a map coordinates system, based on environment sensor data representing an environment of the vehicle, a landmark is detected in the environment, a position of the landmark is determined in the map coordinates system and a second pose of the vehicle is determined in the map coordinates system dependent on the position of the landmark. An assignment instruction is consulted, matching up the first pose with at last one preferred sensor type or at least one dominant landmark type. Depending on the assignment instruction, a first environment sensor system is activated and a second environment sensor system is deactivated, whereupon the environment sensor data are generated by means of the first environment sensor system.

Abstract: According to a method for self-localization of a vehicle, a first pose of the vehicle is determined. Environment sensor data are generated by means of an environment sensor device and on the basis of this a landmark is detected in the environment. A position of the landmark is determined and in dependence on this a second pose of the vehicle is determined. A memorized assignment instruction is consulted, matching up the first pose with at last one preferred sensor type or at least one dominant landmark type, and depending on this a first portion of the environment sensor data is selected that was generated by means of a first environment sensor system of the environment sensor device configured according to a first sensor type. For the detecting of the landmark, a first landmark detection algorithm is applied to the first portion of the environment sensor data.

Abstract: A method for detecting at least one intersection point of road marking lines, wherein a computing unit of a transportation vehicle receives a camera image and identifies a first road marking line based on the camera image. Using the computing unit, a search region is automatically defined in an environment of the first road marking line, and an automatic search limited to the search region is performed. At least one intersection point of the first road marking line with at least a second road marking line is identified as the result of the search.

Abstract: Technologies and techniques for providing a traffic lane localization for a motor vehicle in a region of an infrastructure device and to the motor vehicle. An infrastructure message is received, including at least one portion of traffic lane count information that describes a number of traffic lanes in the region of the infrastructure device. A portion of environment information is provided, which describes an environment of the motor vehicle in the region of the infrastructure device. A portion of adjacent traffic lane information is determined, which describes a number and relative arrangement of adjacent traffic lanes by evaluating the provided environment information. A portion of traffic lane localization information is determined, which describes how the ego traffic lane is localized relative to the adjacent traffic lane by evaluating the received infrastructure message and the determined adjacent traffic lane information. The determined traffic lane localization information is then provided.

Abstract: A device for detecting the surroundings of a vehicle and a method for detecting the surroundings, and a vehicle designed to carry out said method comprise a camera module, a camera control apparatus, an analysis unit and an illumination device. The illumination device is formed by a matrix headlight of the vehicle and is designed such that it can project a light pattern into the surroundings. The projected light pattern is imaged in the detection region of the camera module and the 3D position of measurement points formed by the light pattern in the surroundings is determined by the analysis unit. However, the illumination device projects the light pattern only into regions of the surroundings in which the analysis unit has ascertained, based on image data, a value that is critical for 3D position determination.

Abstract: To determine an absolute position of a vehicle, the vehicle is moved along a trajectory starting from the absolute initial position. The trajectory is sensed by odometry starting from a defined initial position, which is associated with the absolute initial position. Three objects are detected from the vehicle which is on the trajectory. At each detection, a detection beam is sensed. The trajectory with the detection beams are matched with a map. Finally, the absolute initial position is determined from the matching.

Abstract: Disclosed is a method for determining the position of a vehicle, in which highly accurate localization data for positions of the vehicle are determined when traveling along a route. Odometric measured variables for the own odometry of the vehicle are captured when traveling along the route. The highly accurate localization data determined and the odometric measured variables captured are jointly evaluated. The own odometry of the vehicle is corrected on the basis of the evaluation. An error model is used to calculate a vehicle-specific drift for the own odometry of the vehicle and to continually correct the own odometry of the vehicle provided highly accurate localization data can be determined. The corrected own odometry of the vehicle can then be used in areas in which highly accurate localization data cannot be determined in order to determine the position of the vehicle.

Abstract: According to a method for self-localization, a vehicle is detected by a vehicle-external sensor system of a parking infrastructure when it is located in a detection region of the vehicle-external sensor system. By way of a vehicle-external communication interface of the parking infrastructure, position information regarding the detection region is relayed in dependence on the detection of the vehicle to at least one vehicle computer unit and an initial pose of the vehicle is determined by the at least one vehicle computer unit in dependence on the position information.

Abstract: According to a method for self-localization of a vehicle, a first pose of the vehicle is determined. Environment sensor data are generated by means of an environment sensor device and on the basis of this a landmark is detected in the environment. A position of the landmark is determined and in dependence on this a second pose of the vehicle is determined. A memorized assignment instruction is consulted, matching up the first pose with at last one preferred sensor type or at least one dominant landmark type, and depending on this a first portion of the environment sensor data is selected that was generated by means of a first environment sensor system of the environment sensor device configured according to a first sensor type. For the detecting of the landmark, a first landmark detection algorithm is applied to the first portion of the environment sensor data.

Abstract: According to a method for self-localization of a vehicle, a first pose of the vehicle is determined in a map coordinates system, based on environment sensor data representing an environment of the vehicle, a landmark is detected in the environment, a position of the landmark is determined in the map coordinates system and a second pose of the vehicle is determined in the map coordinates system dependent on the position of the landmark. An assignment instruction is consulted, matching up the first pose with at last one preferred sensor type or at least one dominant landmark type. Depending on the assignment instruction, a first environment sensor system is activated and a second environment sensor system is deactivated, whereupon the environment sensor data are generated by means of the first environment sensor system.