Master development requirements
Well thought out data management lays the foundation for conclusive virtual test driving. Simulations generate enormous amounts of data that reach their full potential through effective structuration, clear labeling, and intelligent linking. Maintaining access to traceable and reuseable data is crucial to maximize efficiency in development processes. This approach creates a robust foundation for scalable validation as well as standardized, transparent documentation.
Structured
data storage
Simulations generate massive amounts of data. With a clear filing concept, these data become workable and valuable information. The structuring and versioning of scenarios, parameters, configurations, and results ensure transparency and traceability. This creates a reliable basis for informed decisions in development processes.
The continuous toolchain ensures automated linking and documentation of requirements, tests, scenarios, and results. Test results are thus traceable at all times, including parameterization and version statuses. This seamless traceability enhances transparency, enables reproducible results, and strengthens quality assurance across the entire development process.
Measurement data, test results, and scenarios only take full effect when compared with test requirements. Automated linking within the toolchain creates a consistent and complete data model which lays the foundation for sound analyses, clear decisions, and target-oriented development.
A high number of executed tests entails an accordingly large amount of data. Without scalable data management, test evaluation often becomes a bottleneck. Elaborate data management enables automated storage, quick access, and efficient test evaluations, even with thousands of simulation runs. This ensures high-performing and reliable validation throughout the process.
Individual verifications are not sufficient for technical releases. They require consistent, traceable, and standardized data. Structured documentation provides the foundation for reviews, audits, and registration procedures. It ensures a release process that is efficient, transparent, and compliant.
Use cases
Centralized scenario management for transparent and efficient ADAS development
Centralized management and reutilization of scenarios in ADAS development is key. Scenarios must be linked to requirements and test results while having a clear structure and being easy to find. This makes the development process efficient, traceable and transparent.
Centralized management of results for consistent analyses in the development of electric drives
Centralized management of the results data from simulation and test bench tests of electric drives ensures that these data can be compared and traced across all development stages. Having consistent data also provides a basis for sound analyses and reliable decisions throughout the development process.
Systematic evaluation of safety-critical scenarios to boost the reliability of autonomous driving functions
Autonomous driving functions require extensive long-term testing with a focus on rare and/or safety-critical events. Automated filing and the structured classification of results enable a systematic evaluation that identifies any weak points at an early stage, minimizes risks and improves long-term system reliability.
