MirrorDrive: A Sim-to-Real Bridge for Reproducible Automotive Software Development

A central difficulty in automotive software engineering is to ensure that autonomous driving functions are verified and validated with equal rigor in simulation and on physical vehicles. The transition from virtual development to real-world deployment introduces domain differences in sensor noise, actuator behavior, latency, timing, and environmental conditions, which complicate reproducibility and challenge the reliability of sim-to-real transfer. To address these issues, we present MirrorDrive, an ROS 2-based platform designed to enforce a 'zero code-change' principle. MirrorDrive uses a 1:1 Gazebo simulation model of a physical remote-controlled (RC)-Car platform, allowing the exact same application code to run without adaptation in both environments, enabled by the ROS 2 middleware. The core contribution lies in achieving full deployment consistency by packaging the entire environment and application code within Docker containers. This approach guarantees reproducibility across different systems, supporting Continuous Integration (CI). Our case studies suggest that MirrorDrive provides a scalable and portable framework for the rapid prototyping and reliable validation of autonomous software, making it a valuable testbed for sim-to-real research and education (https://github.com/furkanyondemm/MirrorDrive).