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SilGAN: Generating driving maneuvers for scenario-based software-in-the-loop testing
Upon training, the model uses a concise specification for a driving scenario to generate realistic vehicle state transitions that can occur during such a scenario.
Does the dataset meet your expectations? Explaining sample representation in image data
By mapping the expected distribution of annotations into test samples using parametric simulation, we present a method that explains sample representation using the mismatch in diversity between simulated and collected data.
Controlled time series generation for automotive software-in-the-loop testing using GANs
Testing automotive mechatronic systems partly uses the software-in-the-loop approach, where systematically covering inputs of the system-under-test remains a major challenge.
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