Abstract: A method for processing data with a data processing network including a plurality of data processing modules which each include at least one data processing component, each data processing component being designed for a defined data processing task for processing the data, each data processing module receiving, as input data, data from a data source and/or output data from further data processing modules and generating output data which is network output data of the data processing network and/or input data of further data processing modules. The method for at least one data processing module including: a) receiving a set of input data for performing the data processing tasks; b) receiving a stimulus for activating the at least one data processing component; c) performing the data processing task with the corresponding input data to generate output data; and d) providing the output data.

Abstract: A method for transferring log data from an execution of a computer program. The method includes: generating an indexed list of identifiers of user-defined log-statement-argument data types; before execution of the program, for each log statement of a set of log statements for outputting log data that is contained in the program, transferring static log data to a log data receiver; and, upon execution of the program, for each log statement of the set of log statements that is executed during execution of the program, transferring, dynamic log data for the log statement, and wherein, if the log statement uses one of the user-defined log-statement-argument data types for outputting dynamic log data, the dynamic log data contain an index of the identifier of the log-statement-argument data type.

Abstract: A data processing network for performing successive data processing steps in a redundant and validated manner. Each step is used to generate output data from input data. Output data from a first data processing step are at least partially simultaneously input data of a further data processing step. At least one first data processing module is provided for performing each data processing step. The data processing network also includes a comparator module. The first data processing modules transmit control parameters of the individual data processing steps to the comparator module. The comparator module is provides a synchronized control parameter which contains control information relating to at least one performed data processing step. The data processing network includes a recording module in which a debug mode can be activated with which debug data containing information on each execution of a data processing step with the data processing network are recorded.

Abstract: Method for segmenting a trajectory (1) of a recording run (2) for the swarm-data-based compilation of HD maps, sensor data being acquired along the trajectory (1) during the recording run (2), and the sensor data being able to include GNSS measurement data, comprising the following steps: a) detecting points (4) on the trajectory (1) at which position determination is not possible using GNSS measurement data alone or the accuracy of the position determined using GNSS measurement data alone does not attain a predetermined positioning accuracy, and b) segmenting the trajectory (1) into multiple segments (3) in such a way that each segment (3) attains a predetermined minimum length (5) and that at least one point (4) detected in step a) is located neither in the start region (6) nor in the end region (7) of each segment (3).

Abstract: A data processing network is for performing a plurality of successive data processing steps in a redundant and validated manner. The data processing steps are each used to generate output data from input data. At least some output data from a first data processing step are at the same time input data of a further data processing step. At least a first data processing module and a second data processing module are provided for performing each data processing step. The data processing network includes a comparator module. The first data processing module and the second data processing module are configured to perform the data processing steps, optionally in a first working mode with parallel operation, or in a second working mode with an upstream data processing module and a downstream data processing module.

Abstract: A method processes sensor data from at least two sensors in a vehicle, with a data processing network including a plurality of data processing modules, each including at least one data processing component. Each data processing component is configured for a defined data processing task for processing the sensor data. Each data processing module receives, as input data, the sensor data and/or output data from further data processing modules and generates output data which is network output data of the data processing network and/or input data of further data processing modules. The at least two sensors are subdivided into at least two different resource groups. The method includes receiving at least one parameter and determining at least one priority of a resource group, determining at least one priority for at least one resource group using the at least one parameter, and activating data processing modules based on the determined priorities.

Abstract: A data processing network is for performing a plurality of successive data processing steps in a redundant and validated manner. The data processing steps are each used to generate output data from input data. At least some output data from a first data processing step are at the same time input data of a further data processing step. At least a first data processing module and a second data processing module are provided for performing each data processing step. The data processing network includes a comparator module. The first data processing module and the second data processing module are configured to perform the data processing steps, optionally in a first working mode with parallel operation, or in a second working mode with an upstream data processing module and a downstream data processing module.

Abstract: A data processing network for performing successive data processing steps in a redundant and validated manner. Each step is used to generate output data from input data. Output data from a first data processing step are at least partially simultaneously input data of a further data processing step. At least one first data processing module is provided for performing each data processing step. The data processing network also includes a comparator module. The first data processing modules transmit control parameters of the individual data processing steps to the comparator module. The comparator module is provides a synchronized control parameter which contains control information relating to at least one performed data processing step. The data processing network includes a recording module in which a debug mode can be activated with which debug data containing information on each execution of a data processing step with the data processing network are recorded.

Abstract: A method for processing data, in particular for processing sensor data in a vehicle, using a data processing network. The data processing network has a plurality of data processing modules, which each comprise at least one data processing component, each data processing component being configured for a defined data processing task for processing the data, each data processing module receiving, as input data, data from at least one data source and/or output data from further data processing modules and generating output data which are network output data of the data processing network and/or input data of further data processing modules.

Abstract: A data processing network for the redundant and validated carrying out of successive data processing steps, each used to generate output data from input data. Output data of a first data processing step are at least partially simultaneously input data of a further data processing step. At least a first and a second data processing module carry out each data processing step. The data processing network further comprising a comparator module. The first data processing modules and the second data processing modules transmit control parameters of the individual data processing steps to the comparator module. The comparator module compares corresponding control parameters that were transmitted by the first and second data processing modules. Based on this comparison, the comparator module provides at least one synchronized control parameter that contains an item of control information relating to at least one data processing step that has been carried out.

Abstract: A method for processing data with a data processing network including a plurality of data processing modules which each include at least one data processing component, each data processing component being designed for a defined data processing task for processing the data, each data processing module receiving, as input data, data from a data source and/or output data from further data processing modules and generating output data which is network output data of the data processing network and/or input data of further data processing modules. The method for at least one data processing module including: a) receiving a set of input data for performing the data processing tasks; b) receiving a stimulus for activating the at least one data processing component; c) performing the data processing task with the corresponding input data to generate output data; and d) providing the output data.