Abstract: A method for determining sensor errors and/or localization errors of a vehicle, including: recording a vehicle environment of an ego vehicle by means of at least one environment perception sensor of the ego vehicle; generating an environment representation based on the recording by the environment perception sensor; analyzing the environment representation in the ego vehicle by means of an analysis unit; determining environment information based on the analysis of the environment representation; entering the environment information in an environment model; determining at least one further vehicle in the environment representation from the at least one environment perception sensor of the ego vehicle; transmitting information from the at least one further vehicle to the ego vehicle by means of a vehicle-to-vehicle communication unit; comparing the transmitted information with the environment information from the ego vehicle; determining a sensor error and/or localization error based on the result of the compar

Abstract: In order to recognize hazard areas and/or construction areas on a roadway, an environment sensor produces detected environment data regarding objects indicating the hazard areas and/or construction areas. A traffic light system is detected in the environment data, position data of the traffic light system is determined, an environment scenario is determined from the environment data and is compared with a reference model of the environment scenario. If the reference model does not indicate the presence of a traffic light system, or indicates a traffic light system having position data differing from the position data of the detected traffic light system, then it is concluded that the detected traffic light system is a traffic light system identifying a hazard and/or construction area.

Abstract: Using sensors of a first and second sensor type first and second sensor data are detected and items of information describing identical objects and/or object attributes are allocated to one another in the first and second sensor data. The first and second sensor data are encumbered by first and second ambiguities. Values of the second encumbering ambiguities are at least as great as values of the first encumbering ambiguities. A comparison of the first and second encumbering ambiguities of items of information describing identical objects and/or object attributes takes place. In the case of values of substantially the same size, the items of information describing identical objects and/or object attributes are allocated to one another in the first and second sensor data. In the case of values which are not of substantially the same size the items of information describing identical objects and/or object attributes are confirmed or discarded.

Abstract: The invention relates to a method for determining a reference position as the basis for a correction of a GNSS position of a vehicle located using a Global Satellite Navigation System (GNSS), which contains an absolute position of the vehicle, comprising: recording the absolute position of the vehicle using the GNSS when an output signal (from a motion recording sensor in the vehicle has a characteristic progression; determining the reference position based on the sensed absolute position and assigning the reference position to the characteristic progression of the output signal.

Abstract: In a method for evaluating image data of a vehicle camera, information about raindrops on the vehicle's windshield within the field of view of the camera is taken into account in the evaluation of the image data for detection and classification of objects in the environment of the vehicle. Particularly, for example, depending on the number and the size of the raindrops on the windshield, different detection algorithms, image evaluation criteria, classification parameters, or classification algorithms are used for the detection and classification of objects.

Abstract: A method supports a vehicle's traffic-light-sequence assistant system that detects traffic light sequences of a traffic light (11) with a camera (1). According to the method, when the traffic light (11) is detected in the field of view (1a ) of the camera (1), a length or an end stopping point (L) of a driving path (W) toward the traffic light (11) is determined by a control unit (3), such that the traffic light will remain within view of the camera when the vehicle drives the determined length along the driving path to the end stopping point, and a control signal (St) concerning the determined length (L) or the end stopping point of the driving path (W) is outputted.

Abstract: In a method for determining a course of a traffic lane for a vehicle (10), structures that demarcate a trafficable space are detected in image data from an image acquisition unit (2), and these structures are plotted on a surroundings map (20) that subdivides the surroundings of the vehicle into a two-dimensional grid (20a) of cells (21). The position of the vehicle in the grid of the surroundings map is determined and updated by odometric data. The distance and the direction of the vehicle (10) relative to those cells (21b) of the grid (20a) having structures that demarcate the pavement and/or the traffic lane are determined. Brightness transitions in the image data are detected and are plotted on the cells (21) of the grid (20a). The course of the traffic lane (22) is determined from the cells with the detected brightness transitions.

Abstract: A method and a device are provided for calibrating a plurality of environment sensors in a vehicle. Traffic light signals are detected and identified from the data of at least one environment sensor or from data received by a car-2-X communication unit. A calibration of the plurality of environment sensors is activated and performed in response to a determination that a traffic light signal pertaining to the vehicle has turned red.

Abstract: A method for determining the speed of a vehicle equipped with at least one surround sensor that determines environment data of the vehicle relative to at least one motionless object includes: receiving, by the vehicle, through wireless vehicle-to-environment communication with the at least one motionless object, a transmitted piece of information about the motionlessness of the motionless object; determining the relative motion of the vehicle with respect to the motionless object from the environment data of the vehicle relative to the motionless object; and determining the speed of the vehicle and/or the relative position of the vehicle with respect to the motionless object from the determined relative motion.

Abstract: A method for controlling the starting of a vehicle at a traffic light by a driver assistance system is disclosed. The vehicle starts driving according to whether or not at least one traffic light is present, according to the color phase of the traffic light, and according to the driver's state of attention. A warning signal or a signal for intervening in an acceleration control process of an ego vehicle is output.

Abstract: The invention relates to a method for evaluating image data of a vehicle camera. Information about raindrops on a window within the field of view of the vehicle camera is taken into account in the evaluation of the image data.

Abstract: A method for accelerated object detection or for accelerated object attribute detection, wherein a first information item is acquired by a vehicle-to-X communication device, and describes at least one object or at least one object attribute in an evaluated data form. A second information item is acquired by at least one individual sensor or by a sensor group, and describes the at least one object or the at least one object attribute in sensor raw data form, and an object detection algorithm and/or an object attribute detection algorithm is applied to sensor raw data of the second information item. The method is defined in that a threshold value of the object detection algorithm or of the object attribute detection algorithm for detecting the at least one object or at least one object attribute described by the first information item is reduced in the sensor raw data of the second information item.

Abstract: The invention relates to a method for recognizing marked hazard areas and/or construction areas in the region of lanes, in which method by means of at least one environment sensor the objects indicating hazard areas and/or construction areas are detected. According to the invention a traffic light system is detected by means of the environment sensor, the positional data of the traffic light system is determined, an environment scenario in respect of the environment structure is determined from the environment data detected by the environment sensor and is compared with a reference model of the environment scenario. If said reference model indicates no traffic light system or indicates a traffic light system having positional data differing from the positional data of the detected traffic light system, a conclusion is drawn about a traffic light system identifying a hazard and/or a construction area.

Abstract: Using sensors of a first and second sensor type first and second sensor data are detected and items of information describing identical objects and/or object attributes are allocated to one another in the first and second sensor data. The first and second sensor data are encumbered by first and second ambiguities. Values of the second encumbering ambiguities are at least as great as values of the first encumbering ambiguities. A comparison of the first and second encumbering ambiguities of items of information describing identical objects and/or object attributes takes place. In the case of values of substantially the same size, the items of information describing identical objects and/or object attributes are allocated to one another in the first and second sensor data. In the case of values which are not of substantially the same size the items of information describing identical objects and/or object attributes are confirmed or discarded.

Abstract: The invention relates to a method for determining a course of a traffic lane for a vehicle (10), in which structures that demarcate a space that is fit for traffic are detected by means of at least one image acquisition unit (2) and these structures are plotted on a surroundings map (20) that subdivides the surroundings of the vehicle into a two-dimensional grid structure (20a) of cells (21), wherein the invention provides that the position in the grid structure (21) of the surroundings map (20) is determined and continually updated by means of odometric data of the vehicle (10), the distance and the direction of the vehicle (10) with respect to those cells (21b) of the grid structure (20a) of the surroundings map (20) which feature structures that demarcate the pavement and/or the traffic lane are determined, bright-to-dark and dark-to-bright transitions in the image data generated by the image acquisition unit (2) are detected and are plotted on the cells (21) of the grid structure (20a) of the surroundi

Abstract: The invention relates to a method for supporting a traffic-light-sequence assistant of a vehicle (10), said assistant detecting the traffic light sequences of traffic lights (11) by means of a camera (1). The invention provides that when traffic lights (11) are detected in the visual range (1a) of the camera (1), the length (L) of the driving path (W) in the direction of the traffic lights (11) is determined by means of a control unit (3), said driving path keeping the camera (1) in the visual range (1a) thereof, and a control signal (St) concerning the length (L) of the driving path (W) is outputted.

Abstract: A method for determining the speed of a vehicle equipped with at least one surround sensor that determines environment data of the vehicle relative to at least one motionless object includes: receiving, by the vehicle, through wireless vehicle-to-environment communication with the at least one motionless object, a transmitted piece of information about the motionlessness of the motionless object; determining the relative motion of the vehicle with respect to the motionless object from the environment data of the vehicle relative to the motionless object; and determining the speed of the vehicle and/or the relative position of the vehicle with respect to the motionless object from the determined relative motion.

Abstract: The invention relates to a method and a device for calibrating a plurality of environment sensors in a vehicle. To this end, traffic light signals are detected and identified from the data of at least one environment sensor. The plurality of environment sensors are calibrated when it has been determined that a traffic light signal that is relevant for the vehicle has turned red (R).

Abstract: A method for assisting a vehicle driver, wherein a sensor for covering the surroundings covers a pavement in front of the vehicle in order to determine a virtual vehicle corridor for a road vehicle in a complex traffic situation and the virtual vehicle corridor is determined depending on identified traffic lines and raised pavement boundaries.

Abstract: A method for assisting a vehicle driver, wherein a sensor for covering the surroundings covers a pavement in front of the vehicle in order to determine a virtual vehicle corridor for a road vehicle in a complex traffic situation and the virtual vehicle corridor is determined depending on identified traffic lines and raised pavement boundaries.