Continual Learning for Autonomous Driving Systems

Addressing the challenge of catastrophic forgetting, this research introduces a continual learning paradigm for autonomous driving agents. The proposed methods allow vehicles to continuously learn from new data and adapt to evolving road conditions and scenarios without compromising previously acquired knowledge, enhancing safety and reliability.