AROLA: A Modular Layered Architecture for Scaled Autonomous Racing
This work proposes AROLA, a modular and layered architecture for autonomous racing built upon ROS 2, addressing the limitations of existing fragmented or monolithic systems that lack standardized interfaces and hinder rapid component swapping and objective performance evaluation. AROLA decouples the autonomous driving pipeline into standardized functional layers—including perception, localization, planning, and control—and integrates a lightweight Race Monitor framework to enable real-time data logging and standardized post-race analysis. By enforcing uniform interfaces, the architecture supports plug-and-play module integration and facilitates reproducible benchmarking, significantly enhancing development efficiency and experimental comparability. The proposed system has been validated on both the RoboRacer simulation and physical platforms and was successfully deployed in the RoboRacer IV25 competition in 2025.