Abstract: An at least partially automated guidance of a motor vehicle includes receiving infrastructure-generated environment data describing an environment of the motor vehicle, and deciding, based on the infrastructure-generated environment data, which of three driving strategies to use for the at least partially automated guidance of the motor vehicle. The first driving strategy stipulates that only motor vehicle-generated environment data is used. The second driving strategy stipulates that both the motor vehicle-generated environment data and the infrastructure-generated environment data are used. The third driving strategy stipulates that only the infrastructure-generated environment data is used. On the basis of the decision, control signals for the at least partially automated control of the lateral and/or longitudinal guidance of the motor vehicle are generated and output.

Abstract: A method for identifying an AVP motor vehicle for an AVP process, wherein a driving behavior of the AVP motor vehicle that is manually guided within a region of a parking area is determined on the motor vehicle side, wherein the driving behavior determined on the motor vehicle side is compared with a driving behavior, determined on the infrastructure side, of a motor vehicle located in the same region of the parking area or a plurality of motor vehicles located in the same region of the parking area in order to identify the AVP motor vehicle. Furthermore a method for identifying an AVP motor vehicle for an AVP process, to a device, to a motor vehicle, to a computer program, to a machine-readable storage medium and to a system for identifying an AVP motor vehicle for an AVP process.

Abstract: A method for monitoring, on the infrastructure side, a highly automated journey of a motor vehicle within a parking area, including the steps of receiving, on the infrastructure side, motor vehicle state data which are transmitted by the motor vehicle during an at least highly automated AVP type 1 journey within the parking area and describe a motor vehicle state during the at least highly automated AVP type 1 journey of the motor vehicle, and monitoring, on the infrastructure side, the at least highly automated AVP type 1 journey of the motor vehicle on the basis of the received motor vehicle state data. An AVP system for a parking area, to a method for at least highly automated driving of a motor vehicle, to an AVP system for a motor vehicle, to a motor vehicle, to a computer program and to a machine-readable storage medium.

Abstract: A method for driving a motor vehicle within a parking area includes providing the motor vehicle with a motor vehicle AVP system, and operating the motor vehicle in a second AVP operating mode by way of the motor vehicle AVP system, with the motor vehicle driving according to an AVP type 2 within the parking area with the assistance of an infrastructure AVP. A handover process is carried out to switch the motor vehicle from the second AVP operating mode to a first AVP operating mode when a handover region of the parking area is reached by the motor vehicle, with the switching occurring when the handover process has been completed. The motor vehicle is operated in the first AVP operating mode after switching, with the motor vehicle driving according to the AVP type 1 within the parking area.

Abstract: A method for detecting a decalibration of a surroundings sensor involves using the surroundings sensor to detect a number of objects in the surroundings. Angular velocities of the detected objects are determined while the vehicle is travelling. Clusters of a number of the objects are determined by a histogram evaluation based on the angular velocities. A decalibration of the surroundings sensor is identified if a cluster is found beyond an angular velocity of zero, which is caused by a deviation of the orientation of the surroundings sensor from a normal position relative to a vehicle axis of the vehicle.

Abstract: A method for detecting a decalibration of a surroundings sensor involves using the surroundings sensor to detect a number of objects in the surroundings. Angular velocities of the detected objects are determined while the vehicle is travelling. Clusters of a number of the objects are determined by a histogram evaluation based on the angular velocities. A decalibration of the surroundings sensor is identified if a cluster is found beyond an angular velocity of zero, which is caused by a deviation of the orientation of the surroundings sensor from a normal position relative to a vehicle axis of the vehicle.

Abstract: The present invention relates to plasmonic components, more particularly plasmonic waveguides, and to plasmonic photodetectors that can be used in the field of microoptics and nanooptics, more particularly in highly integrated optical communications systems in the infrared range (IR range) as well as in power engineering, e.g. photovoltaics in the visible range. The present invention also specifies a method for producing a plasmonic component, more particularly for photodetection on the basis of internal photoemission.

Abstract: The present invention relates to plasmonic components, more particularly plasmonic waveguides, and to plasmonic photodetectors that can be used in the field of microoptics and nanooptics, more particularly in highly integrated optical communications systems in the infrared range (IR range) as well as in power engineering, e.g. photovoltaics in the visible range. The present invention also specifies a method for producing a plasmonic component, more particularly for photodetection on the basis of internal photoemission.