EXPLORING THE POTENTIAL OF NEURAL NETWORKS IN AUTONOMOUS VEHICLES

Neural networks have become integral to the advancement of autonomous vehicles, offering sophisticated solutions for environmental perception, decision-making, and control systems. Their application has significantly enhanced the ability of self-driving cars to interpret complex environments and make informed driving decisions. The following article is focusing on enhancing the interpretability of neural networks through Explainable AI (XAI), improving adaptability via transfer learning, and increasing robustness against adversarial attacks. Innovations in energy-efficient neural network architectures are also underway to facilitate deployment in resource-constrained environments, such as electric vehicles.