Abstract

Worldwide, initiatives strive for developing highly automated road vehicles of SAE levels 3 and above. Due to the complexity of the open world, requirements for those systems cannot be collected, engineered, and tracked the same way, as it has been established for ‘conventional’ products over the last decades. Correspondingly, highly automated vehicles cannot be verified and homologated ‘as usual’ solely by testing them against classical requirements using ‘conventional’ test catalogs. Instead, new approaches such as scenario-based approaches are needed to verify the vehicle’s correct behavior, especially under critical circumstances. Finding these critical scenarios is one challenge, which can be addressed by applying DOE-similar methods to parameterized families of scenarios. Another is investigating the vehicle’s behavior within such scenarios. [WW15] states that statistically some 1.000.000.000 km need to be driven to verify a highly automated vehicle by physical test for homologation. It is unclear, how many of these test kilometers would have to be repeated after each software iteration. Moreover, physical tests approach their technical limits when it comes to urban traffic scenarios involving pedestrians and other vulnerable road users (VRUs). Both renders classical physical test insufficient for verification and homologation of highly automated vehicles. The solution can only be virtual test, also known as simulation. The amount of virtually driven km scales with computing power, but does not require more engineers, if scenarios are generated automatically. This is the reason why scenario-based testing got the focus in recent years. A system enabling a vehicle to reach SAE levels 3 and above is highly sophisticated and requires highly developed systems engineering processes, capabilities, methods, tools, and even standards. We address these challenges by modern methods, which enable simulation-based decision making, analysis and verification. Methods are derived from model-based systems engineering (MBSE), and will guide us seamlessly all the way down from high level systems architecture to implementable simulation model prototypes. To reach this goal, we apply the RFLP-pattern to the system of the complete simulation, composed of not only the simulation model, but also the simulation software. Diversity and complexity of real traffic participants is tackled by a frame model with configurable components. This all is shown within the context of a credible simulation process, cf. [GH20, Hei21, HV20]. As modeling language, a subset of UML is used. This guarantees that the method is easy to understand and agnostic of the modeling tool. This new approach is explained using a practical application as example.