Attack End-to-End Autonomous Driving through Module-Wise Noise
Attack End-to-End Autonomous Driving through Module-Wise Noise
With recent breakthroughs in deep neural networks, numerous tasks within autonomous driving have exhibited remarkable performance. However, deep learning models are susceptible to adversarial attacks, presenting significant security risks to autonomous driving systems. Presently, end-to-end architectures have emerged as the predominant solution for autonomous driving, owing to their collaborative nature …