Comprehensive Analysis of End-to-end Autonomous Driving: Challenges, Methodologies, and Future Directions
End-to-end autonomous driving systems that directly map raw sensor inputs to vehicle motion plans offer several advantages over modular pipelines, including joint feature optimization, computational efficiency, and data-driven optimization. However, this emerging field faces critical challenges such as multi-modality, interpretability, causal confusion, robustness, and world model learning.