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A Novel Model for Driver Lane Change Prediction in Cooperative Adaptive Cruise Control Systems
Accurate lane change prediction can reduce potential accidents and contribute to higher road safety.
LSTM-based Preceding Vehicle Behaviour Prediction during Aggressive Lane Change for ACC Application
To this end, the proposed system was assessed on a simulated driving environment and compared with a feedforward Artificial Neural Network (ANN) model and Model Predictive Control (MPC) model.
Transferable Universal Adversarial Perturbations Using Generative Models
Using our generated non-targeted UAPs, we obtain an average fooling rate of 93. 36% on the source models (state of the art: 82. 16%).
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