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EnergyShield: Provably-Safe Offloading of Neural Network Controllers for Energy Efficiency
To mitigate the high energy demand of Neural Network (NN) based Autonomous Driving Systems (ADSs), we consider the problem of offloading NN controllers from the ADS to nearby edge-computing infrastructure, but in such a way that formal vehicle safety properties are guaranteed.
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