This thesis researches into the assessment of automated driving functions as existing methods are stretched to their limits. A scenario-based methodology incorporating virtual testing is elaborated and implemented in a proof of concept manner. In this context, a risk metric for driving tests and a framework for the re-simulation and cross-verification with real-world driving tests are proposed. Further, this thesis provides tooling for variation of scenarios and the definition of a scenario space for coverage estimation.
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This thesis researches into the assessment of automated driving functions as existing methods are stretched to their limits. A scenario-based methodology incorporating virtual testing is elaborated and implemented in a proof of concept manner. In this context, a risk metric for driving tests and a framework for the re-simulation and cross-verification with real-world driving tests are proposed. Further, this thesis provides tooling for variation of scenarios and the definition of a scenario spac...
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