Securing and homologating automated driving functions presents a huge challenge for their market introduction due to an enormous number of scenarios and environment parameter combinations. Confronting conventional real world tests with the new challenges of automated driving is not feasible anymore and yields to a virtualization of the testing methods by means of X-in-the-Loop approaches. Since their validity is a key enabler for virtual homologation, this paper focuses on the validation of X-in-the-Loop approaches. A generic validation methodology is introduced and demonstrated for the specific use case of an automated longitudinal driving function. As a proof of concept equal scenarios are performed in real driving tests as reference and in two X-in-the-Loop approaches based on a test bed resp. a purely virtual co-simulation environment. The paper describes how a consistent implementation can be ensured to evaluate the collected data. First results show a promising correlation regarding multiple repetitions on the test bed and regarding the validation of both X-in-the-Loop approaches for a future virtual homologation of automated driving functions.
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Securing and homologating automated driving functions presents a huge challenge for their market introduction due to an enormous number of scenarios and environment parameter combinations. Confronting conventional real world tests with the new challenges of automated driving is not feasible anymore and yields to a virtualization of the testing methods by means of X-in-the-Loop approaches. Since their validity is a key enabler for virtual homologation, this paper focuses on the validation of X-in...
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