AINeutralarXiv – CS AI · 7h ago6/10
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Reinterpreting Safety Thresholds as Neuron Spiking Thresholds
Researchers propose a biologically-inspired approach to safety thresholds in autonomous driving by modeling Surrogate Safety Measures (SSMs) as leaky integrate-and-fire neuron spiking thresholds within a spiking neural network. Trained on human braking data from controlled experiments, the SNN captures dynamic safety responses that fixed thresholds miss, potentially bridging the gap between objective risk metrics and subjective human perception.