Abstract: A computer-implemented method for filtering operating scenarios during the operation of a vehicle. The method includes receiving at least one time series of data, storing time-ordered data points of the at least one time series of data in a first memory, generating a trace diagram for the time-ordered data points stored in the first memory, checking whether the trace diagram generated is new in comparison to one or more existing trace diagrams, and storing the time-ordered data points stored in the first memory, in a second memory if the trace diagram generated is new.

Abstract: A computer-implemented method for identifying corner cases of operating scenarios of vehicles. The method includes receiving one or multiple feature(s) for characterizing an operating state of a vehicle, extracting at least one trace graph relating to the one or to the multiple feature(s) from a graph database, modifying the at least one trace graph, a modified trace graph being generated, reconstructing a first operating scenario from the trace graph, reconstructing a second operating scenario from the modified trace graph, and identifying the second operating scenario as a corner case if the second operating scenario is assessed as new and/or as unknown as compared to the first operating scenario on the basis of a predetermined criterion.

Abstract: A computer-implemented method for generating an operating scenario of a vehicle based on a trace graph. The method includes obtaining the trace graph, selecting a trace in the trace graph, and reconstructing an operating scenario of a vehicle from the trace of the trace graph. A computer-implemented method for generating a trace graph for one or multiple time recordings of an operating scenario of a vehicle is also provided, including clustering y values of the one or multiple time recordings into at least two clusters in a space whose dimensionality corresponds to the number of the one or multiple time recordings, optionally with the aid of unsupervised learning, identifying at least one cluster as a node in the trace graph, analyzing the transitions between clusters, based on the one or multiple time recordings, and identifying at least one transition as an edge between two nodes in the trace graph.

Abstract: A computer-implemented method for collecting sensor data of a vehicle. The method includes receiving of request data that describe at least one data record missing in an existing field data record, in the vehicle. The method furthermore includes a continuous recording of sensor data for the vehicle while the vehicle is in operation and storing recorded sensor data in a short-term memory. The method also includes receiving an acknowledge signal to the effect that certain recorded sensor data correspond to a missing data record, and storing the certain recorded sensor data in a second memory before the recorded sensor data are deleted from the short-term memory.

Abstract: A method for rating a software component of a software-in-the-loop (SiL) environment, a target hardware including at least one target hardware component being simulated by an SiL environment including at least one corresponding software component, both the target hardware and the SiL environment being subjected to a test situation, while the target hardware and the SiL environment are being subjected to the test situation, output data being generated in each case by both the target hardware and the SiL environment and the output data of the target hardware being compared to the outputs of the SiL environment, the software component being rated on the basis of the comparison.

Abstract: A method for rating a software component of a software-in-the-loop (SiL) environment, a target hardware including at least one target hardware component being simulated by an SiL environment including at least one corresponding software component, both the target hardware and the SiL environment being subjected to a test situation, while the target hardware and the SiL environment are being subjected to the test situation, output data being generated in each case by both the target hardware and the SiL environment and the output data of the target hardware being compared to the outputs of the SiL environment, the software component being rated on the basis of the comparison.