Using simulation to validate and homologate ADAS/AD

The combined expertise of both companies makes the smart and highly automatic validation of ADAS/AD systems possible and forms the basis for homologation.

Tremendous developments in the fields of advanced driver assistance systems (ADAS) and functions for automated driving (AD) continue to face major challenges related to validation at the system level, as well as safety.

Virtual and scalable simulation solutions with efficient processes for data management, test creation, simulation, and evaluation, including a risk analysis, are indispensable for exploiting the potential of automation and launching autonomous driving functions onto the street. BTC and dSPACE have created a special solution just for this purpose.

dSPACE a supplier 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, custom solutions are available for testing ECU software and electronics at the component, system, and vehicle level and for validating safety.

The dSPACE V&V environment allows for a seamless transition between different test levels and constant SIL and HIL validation when reusing tests on a regular basis. Based on dSPACE’s established Automotive Simulation Models (ASM), the new web-based solution for simulation and validation, SIMPHERA, will be available for use in general customer projects starting the second half of this year. The highly scalable and intuitive environment for validating ADAS/AD systems can be used on site or in the cloud, thus making collaborative use and access from anywhere possible.

BTC is a leading manufacturer of software test and verification tools in the international automotive sector. The BTC ScenarioPlatform offers a highly automated solution for creating scenarios, generating tests, and evaluating tests based on coverage. Graphical traffic scenarios can be created intuitively using the BTC ScenarioComposer. The high level of abstraction makes it possible to express  thousands of test cases with just one abstract scenario.

The automated test generation functionality uses advanced technology such as model checking and AI, and thanks to the intelligent weakness detection, it allows test cases to be generated efficiently based on statistical methods and meaningful coverage metrics.

In contrast to random or ‘brute force’ test generation approaches, this strategy reduces the amount of test data considerably and at the same time delivers clear metrics, making it possible to determine when the test activities have been completed even with regard to future homologation criteria. The simulations are evaluated automatically by the BTC RuleObserver to ensure compliance with traffic rules or safety objectives.