This paper reviews the current state of autonomous driving, identifies limitations in scalability and adaptability, and proposes a data-driven, two-stage fine-tuning process and a "service-oriented modular end-to-end (SO-M-E2E)" architecture to achieve fully autonomous driving while integrating technological and socio-political aspects.

This paper introduces a modular architecture for autonomous vehicles designed for racing in closed circuits. It integrates perception, localization, path planning, and control subsystems to achieve real-time, precise autonomous navigation in controlled environments.