Abstract: A method for operating a higher-level automated vehicle (HAV), in particular a highly automated vehicle, is provided, including: S1 for providing a digital map, which may be a highly accurate digital map, in a driver assistance system of the HAV; S2 for determining an instantaneous vehicle position and localizing the vehicle position in the digital map; S3 for providing an expected setpoint traffic density at the vehicle position; S4 for ascertaining an instantaneous actual traffic density in the surroundings of the HAV; S5 for comparing the actual traffic density to the setpoint traffic density and ascertaining a difference value as the result of the comparison; S6 for checking the vehicle position of the HAV for plausibility at least partially based on the difference value and/or S7 for updating the digital map at least partially based on the difference value. Also described are a corresponding driver assistance system and a computer program.

Abstract: A method for operating a more highly automated vehicle (HAF), in particular a highly automated vehicle, including: S1—providing a digital map or a highly accurate digital map, in a driver-assistance-system of the HAF; S2—determining a current vehicle position and locating the vehicle position in the digital map; S3—providing at least one expected feature property of at least one feature in a surroundings of the HAF; S4—detecting at least one actual feature property of a feature in the surroundings of the HAF at least partially on the basis of the expected feature property; S5—comparing the actual feature property with the expected feature property and ascertaining at least one differential value; S6—checking the plausibility of the actual feature property at least partially on the basis of the differential value. Also described is a corresponding system and a computer program.

Abstract: A method and corresponding system and computer program for a highly-automated-vehicle (HAV), the method including: providing a digital-map; determining a present vehicle-position relative to the digital-map; providing at least one setpoint property of at least one feature in an HAV-environment; using at least one sensor to detect at least one actual property of a feature in the HAV-environment based at least in part on the setpoint property; comparing the actual property to the setpoint property and determining at least one difference-value based on the comparison; and verifying the digital-map, the digital-map being classified as not up-to-date if the difference-value reaches/exceeds a specified-threshold-value of a deviation, and being classified as up-to-date if the difference-value remains below the specified-threshold-value of the deviation.

Abstract: A surroundings detection system for motor vehicles, including multiple sensors which are sensitive to electromagnetic radiation in different ranges of the electromagnetic spectrum, and including associated evaluation modules for locating and/or classifying objects present in the surroundings based on the data supplied by the sensors, including a model module in which a surroundings model is stored which, in addition to the 3D position data of the objects, also contains data about the spectral reflection properties of surfaces of the objects, the model module being capable of providing these data to the evaluation modules.

Abstract: A method for carrying out a prediction of a driving behavior of a second vehicle by a control unit of a first vehicle. Data of vehicle surroundings of the second vehicle, and/or data of a vehicle driver and/or of a load of the second vehicle being received by the control unit, at least one feature being ascertained based on the data and a likely driving behavior of the second vehicle being calculated by the control unit based on the ascertained feature. A control unit is also described.

Abstract: A control unit for a vehicle for analyzing localization systems, the control unit being connectable in a data-conducting manner to at least two localization systems which are operable independently of one another for ascertaining system-specific positions, each localization system including at least one sensor, the control unit being configured to evaluate pieces of position information ascertained by the localization systems by subjecting them to a plausibility check. Also described are a related method and a sensor system.

Abstract: A method and a device for determining a highly precise position of a vehicle. The method includes a step of sensing environment data values, which represent an environment of the vehicle, the environment encompassing multiple environment features which have at least one regular structure, and the environment data values at least encompassing the at least one regular structure; a step of carrying out a comparison of the environment data values with a map; a step of determining the highly precise position of the vehicle as a function of the comparison; and a step of supplying a signal on the basis of the highly precise position.

Abstract: A method for locating a highly automated vehicle (HAV) in a digital location map, including: providing a digital map in a driver assistance system of the HAV; determining a current vehicle position, and locating the vehicle position in the digital map; identifying a route segment currently traveled by the HAV in the digital map; providing at least one traveled comparison trajectory of at least one additional vehicle along the currently traveled route segment; comparison of the at least one comparison trajectory with the currently traveled route segment as indicated in the digital map, and ascertaining a difference value as a result of the comparison; and ascertaining an up-to-dateness of the currently traveled route segment in the digital map, at least partly on the basis of the difference value.

Abstract: A method for predicting a construction-related driving-route change of a driving route for a vehicle includes at least a step of reading in and a step of detecting. In the step of reading in, at least one image signal is read in, which represents an image, recorded by the vehicle, of a construction-site parameter in the environment of the driving route. In the step of detecting, the impending driving-route change is detected using the image signal.

Abstract: A method for operating a more highly automated vehicle (HAF), in particular a highly automated vehicle, including: S1—providing a digital map or a highly accurate digital map, in a driver-assistance-system of the HAF; S2—determining a current vehicle position and locating the vehicle position in the digital map; S3—providing at least one expected feature property of at least one feature in a surroundings of the HAF; S4—detecting at least one actual feature property of a feature in the surroundings of the HAF at least partially on the basis of the expected feature property; S5—comparing the actual feature property with the expected feature property and ascertaining at least one differential value; S6—checking the plausibility of the actual feature property at least partially on the basis of the differential value. Also described is a corresponding system and a computer program.

Abstract: A method for operating a higher-level automated vehicle (HAV), in particular a highly automated vehicle, is provided, including: S1 for providing a digital map, which may be a highly accurate digital map, in a driver assistance system of the HAV; S2 for determining an instantaneous vehicle position and localizing the vehicle position in the digital map; S3 for providing an expected setpoint traffic density at the vehicle position; S4 for ascertaining an instantaneous actual traffic density in the surroundings of the HAV; S5 for comparing the actual traffic density to the setpoint traffic density and ascertaining a difference value as the result of the comparison; S6 for checking the vehicle position of the HAV for plausibility at least partially based on the difference value and/or S7 for updating the digital map at least partially based on the difference value. Also described are a corresponding driver assistance system and a computer program.

Abstract: A method is described for verifying a digital map of a higher-level automated vehicle (HAV), in particular a highly automated vehicle, including the steps: S1 providing a digital map, preferably a highly accurate digital map: S2 determining an instantaneous reference position and localizing the reference position in the digital map; S3 establishing at least one actual feature property of a feature in the surroundings of the reference position, the establishment being carried out with the aid of at least one information source; S4 comparing the actual feature property to a setpoint feature property of the feature and ascertaining at least one difference value as the result of the comparison. A corresponding device and a computer program are also described.

Abstract: A method for verifying a digital-map of a more highly-automated-vehicle (HAV), especially of an HAV, including: S1—providing a digital-map or a highly accurate digital-map, in an HAV driver-assistance-system; S2—determining a present vehicle-position and locating the vehicle-position in the digital-map; S3—providing at least one setpoint-feature-property of at least one feature in an HAV-environment; S4—detecting at least one actual-feature-property of a feature in the HAV-environment based at least in part on the setpoint-feature-property, the detection being performed with at least one sensor; S5—comparing the actual-feature-property to the setpoint-feature-property and determining at least one difference-value based on the comparison; S6—verifying the digital-map based at least in part on the difference-value, the digital-map being classified as not up-to-date if the difference-value reaches/exceeds a specified-threshold-value of a deviation, and being classified as up-to-date if the difference-value remai

Abstract: A control unit for a vehicle for analyzing localization systems, the control unit being connectable in a data-conducting manner to at least two localization systems which are operable independently of one another for ascertaining system-specific positions, each localization system including at least one sensor, the control unit being configured to evaluate pieces of position information ascertained by the localization systems by subjecting them to a plausibility check. Also described are a related method and a sensor system.

Abstract: A surroundings detection system for motor vehicles, including multiple sensors which are sensitive to electromagnetic radiation in different ranges of the electromagnetic spectrum, and including associated evaluation modules for locating and/or classifying objects present in the surroundings based on the data supplied by the sensors, including a model module in which a surroundings model is stored which, in addition to the 3D position data of the objects, also contains data about the spectral reflection properties of surfaces of the objects, the model module being capable of providing these data to the evaluation modules.

Abstract: A method, a processing unit which carries out the method, and a system including the processing unit for updating a digital map for locating motor vehicles are provided. In the case of the method for updating a digital map for locating motor vehicles, surroundings information is detected by a vehicle for the purpose of updating the digital map and the detected surroundings information is compared to the surroundings information which is stored on the digital map. In this case, the vehicle is located on the digital map, which means that the location or position of the vehicle on the digital map is known. For the purpose of detecting the surroundings information, the vehicle is navigated along a first route, whose most recently carried out comparison of surroundings information dates back the longest as compared to at least one further optional route.

Abstract: A method for predicting a construction-related driving-route change of a driving route for a vehicle includes at least a step of reading in and a step of detecting. In the step of reading in, at least one image signal is read in, which represents an image, recorded by the vehicle, of a construction-site parameter in the environment of the driving route. In the step of detecting, the impending driving-route change is detected using the image signal.