Abstract: A method for identifying and classifying static radar targets with the aid of a radar sensor of a motor vehicle. The method includes: identifying an object as a static radar target based on the received radar signals reflected by the object, generating an occupancy pattern in an occupancy grid based on the received radar signals reflected by the object, storing an assignment, which assigns the generated occupancy pattern to the static radar target, classifying the static radar target as belonging to one or multiple groups of static radar targets based on characteristic features of radar signatures of the received radar signals reflected by the corresponding object. A radar sensor is also described.

Abstract: A method for fusing environment-related parameters includes providing at least one environment-related parameter of a first sensor system; providing at least one environment-related parameter of a second sensor system; providing at least one respective boundary condition that existed when the respective at least one environment-related parameter of the respective sensor system was determined; assigning the at least one respective boundary condition to the respective at least one environment-related parameter of the respective sensor system; providing an evaluation scheme which assigns weighting factors to the respective environment-related parameter of the respective sensor system depending on the respective boundary conditions; and fusing, with a fusion device, the at least one environment-related parameter of the first sensor system with the at least one environment-related parameter of the second sensor system according to the assigned weighting factors to determine the representation of the environment of

Abstract: A method for determining the reliability of detected and/or tracked objects for use in the driver assistance or the at least semiautomated driving of a vehicle. The method includes: a) receiving sensor data for the detected objects from a plurality of sensors, b) associating pieces of object existence information with each object, c) checking, considering, or representing redundancy of pieces of object existence information.

Abstract: A method for monitoring a vehicle system configured to detect an environment of a vehicle, wherein the vehicle system has a sensor system with at least two sensor units configured to capture the environment of the vehicle, and an evaluation unit configured to detect objects in the environment of the vehicle by merging sensor data of the at least two sensor units. The method includes, for each of the detected objects, using sensor data to determine separately for each of the at least two sensor units a probability of existence indicating a probability of the detected object representing a real object, and a probability of detection indicating a probability with which the detected object can be captured by the sensors. The method includes determining whether the vehicle system is in a robust state based on the probability of existence and the probability of detection.

Abstract: A system and method for determining if a field calibration of a subject sensor associated with a vehicle is warranted, and calibrating the subject sensor using a sensor associated with another vehicle when calibration is warranted. Reference vehicles may perform predetermined maneuvers in order to provide additional measurements for use during calibration.

Abstract: A system and method of sensor validation utilizing a sensor-fusion network. The sensor-fusion network may comprise a number of sensors associated with one or more vehicles having autonomous or partially autonomous driving functions.

Abstract: A method for evaluating locating measurements of a surroundings sensor for a motor vehicle. The method includes: associating locating measurements with an object described by an estimated object state, for the locating measurements in each case an association probability being determined for the association of the locating measurement with the object; estimating instantaneous state parameters of the object, including an adaptation of the state parameters to the locating measurements associated with the object, weightings of the locating measurements associated with the object being taken into consideration during the adaptation, for the locating measurements in each case the weighting being dependent on the determined association probability for the association of the particular locating measurement with the object; and transferring the estimated instantaneous state parameters of the object to a state estimator for updating the estimated state of the object. A sensor system is also described.

Abstract: A method for monitoring a vehicle system configured to detect an environment of a vehicle, wherein the vehicle system has a sensor system with at least two sensor units configured to capture the environment of the vehicle, and an evaluation unit configured to detect objects in the environment of the vehicle by merging sensor data of the at least two sensor units. The method includes, for each of the detected objects, using sensor data to determine separately for each of the at least two sensor units a probability of existence indicating a probability of the detected object representing a real object, and a probability of detection indicating a probability with which the detected object can be captured by the sensors. The method includes determining whether the vehicle system is in a robust state based on the probability of existence and the probability of detection.

Abstract: A method for identifying and classifying static radar targets with the aid of a radar sensor of a motor vehicle. The method includes: identifying an object as a static radar target based on the received radar signals reflected by the object, generating an occupancy pattern in an occupancy grid based on the received radar signals reflected by the object, storing an assignment, which assigns the generated occupancy pattern to the static radar target, classifying the static radar target as belonging to one or multiple groups of static radar targets based on characteristic features of radar signatures of the received radar signals reflected by the corresponding object. A radar sensor is also described.

Abstract: A method for creating an inverse sensor model for a radar sensor system. The method comprises: placing obstacles having predefined dimensions and spatial positions in a surrounding field of the radar sensor system; the radar sensor system generating radar measurement data; and generating the inverse sensor model using the generated radar measurement data and the predefined dimensions and spatial positions of the obstacles, the inverse sensor model assigning an occupancy probability as a function of predefined radar measurement data to a cell of an occupancy grid.

Abstract: A system and method of sensor validation utilizing a sensor-fusion network. The sensor-fusion network may comprise a number of sensors associated with one or more vehicles having autonomous or partially autonomous driving functions.

Abstract: A system and method for determining if a field calibration of a subject sensor associated with a vehicle is warranted, and calibrating the subject sensor using a sensor associated with another vehicle when calibration is warranted. Reference vehicles may perform predetermined maneuvers in order to provide additional measurements for use during calibration.

Abstract: A method is described for avoiding or mitigating a collision of a vehicle with an obstacle in a traffic lane of the vehicle, if the obstacle is at least partially blocking a planned travel envelope of the vehicle, the method including a step of detecting and a step of adapting. In the step of detecting, a position and/or trajectory of the obstacle is detected. In the step of adapting, the travel envelope is adapted with the aid of the position and/or the trajectory, in order to avoid or mitigate the collision.

Abstract: A method for guiding a vehicle in the surrounding environment of an object. The method includes reading in a multiplicity of view ray endpoints in a three-dimensional image, produced by a stereo camera of the vehicle, of a surrounding environment, containing the object, of the vehicle, at least one of the view ray endpoints representing an outer surface of the object, connecting the multiplicity of view ray endpoints to form a polygon that represents a free surface to be traveled by the vehicle, and generating a driving corridor, provided for the vehicle, for driving around the object, based on the free surface.

Abstract: A method for classifying a behavior, of a pedestrian when crossing a roadway of a vehicle, includes reading in a sensor signal to detect the pedestrian and at least one piece of surroundings information regarding surroundings of the pedestrian. The sensor signal represents here a signal of at least one sensor of the vehicle. The method further includes ascertaining at least one physical variable of a correlation between the pedestrian and the at least one piece of surroundings information. Finally, the method includes classifying the behavior of the pedestrian using the at least one physical variable.

Abstract: In a method for ascertaining the stress level of the driver, the setpoint trajectory of the vehicle is ascertained and compared to the actual trajectory. A higher stress level is inferred from an increasing frequency and/or magnitude of the deviation of the actual trajectory from the setpoint trajectory.

Abstract: A method for guiding a vehicle in the surrounding environment of an object. The method includes reading in a multiplicity of view ray endpoints in a three-dimensional image, produced by a stereo camera of the vehicle, of a surrounding environment, containing the object, of the vehicle, at least one of the view ray endpoints representing an outer surface of the object, connecting the multiplicity of view ray endpoints to form a polygon that represents a free surface to be traveled by the vehicle, and generating a driving corridor, provided for the vehicle, for driving around the object, based on the free surface.

Abstract: A method for classifying a behavior, of a pedestrian when crossing a roadway of a vehicle, includes reading in a sensor signal to detect the pedestrian and at least one piece of surroundings information regarding surroundings of the pedestrian. The sensor signal represents here a signal of at least one sensor of the vehicle. The method further includes ascertaining at least one physical variable of a correlation between the pedestrian and the at least one piece of surroundings information. Finally, the method includes classifying the behavior of the pedestrian using the at least one physical variable.

Abstract: A method is described for avoiding or mitigating a collision of a vehicle with an obstacle in a traffic lane of the vehicle, if the obstacle is at least partially blocking a planned travel envelope of the vehicle, the method including a step of detecting and a step of adapting. In the step of detecting, a position and/or trajectory of the obstacle is detected. In the step of adapting, the travel envelope is adapted with the aid of the position and/or the trajectory, in order to avoid or mitigate the collision.

Abstract: In a method for ascertaining the stress level of the driver, the setpoint trajectory of the vehicle is ascertained and compared to the actual trajectory. A higher stress level is inferred from an increasing frequency and/or magnitude of the deviation of the actual trajectory from the setpoint trajectory.