This paper presents the verification of FSDSS232 , a synthetic dataset designed for testing perception modules under adversarial conditions. We propose a verification pipeline combining statistical model checking and adversarial perturbation analysis. Our results show that the model trained on FSDSS232 achieves 98.7% verified safety under defined operational design domain constraints.
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