AI in autonomous vehicles is evolving through advancements in perception, decision-making, and control systems. Perception models analyze data from cameras, LiDAR, and radar to detect objects, identify lanes, and understand traffic scenarios.
Decision-making systems use reinforcement learning and deep neural networks to plan routes and respond to dynamic environments. For instance, Tesla’s Autopilot employs AI to perform adaptive cruise control and self-parking.
Innovations like edge computing and federated learning are also enhancing the real-time processing and safety of AI systems, driving the evolution of autonomous vehicle technology.