dSPACE, BTC join forces for ADAS simulation and validation
Advances in advanced driver assistance systems (ADAS) and automated driving (AD) functions continue to face major challenges in the area of system-level validation and proof of safety. Virtual and scalable simulation solutions with efficient processes for data management, test creation, simulation and evaluation, including risk analysis, are seen as indispensable in many areas of the industry in order to leverage automation potential and bring automated driving functions to the road. BTC and dSPACE are now creating a concrete offer for this in the form of a combined solution. It is based on the seamless integration of BTC’s ScenarioPlatform into dSPACE’s Simphera simulation and validation environment.
dSPACE sees itself as a leading provider of solutions for simulation-based verification and validation (V&V) at all system levels in the automotive industry. Based on highly realistic simulation models and digital twins, corresponding solutions are available for testing ECU software and electronics at component, system, and vehicle level, right through to safety validation. The dSPACE V&V environment enables seamless transition between different test levels and consistent SIL and HIL validation with consistent test reuse.
Based on the established Automotive Simulation Models (ASM), Simphera, the new web-based solution for simulation and validation, will be available for use in general customer projects from the second half of this year. The highly scalable environment for validating ADAS/AD systems can be used on-site or in the cloud, allowing collaborative use and access from anywhere in the world.
BTC has made a name for itself with the development of software testing and verification tools in the automotive sector. The company’s ScenarioPlatform offers a highly automated solution for scenario creation, test generation and coverage-based test evaluation. Traffic scenarios can be created with the BTC ScenarioComposer using graphical methods. The high level of abstraction allows thousands of test cases to be expressed with only one abstract scenario. The automatic test generation uses technologies such as model checking and AI, and thanks to intelligent vulnerability analysis, enables the efficient generation of test cases based on statistical methods and meaningful coverage metrics. In contrast to random or “brute-force” test generation approaches, this strategy significantly reduces the amount of test data and at the same time provides unambiguous metrics that allow to assess when the test activities are completed also with regard to future homologation criteria. The evaluation of the simulations with regard to traffic rules or safety targets is carried out automatically by the BTC RuleObserver.
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