Continuous Development and Safety Assurance Pipeline for ML-Based Systems in the Railway Domain

Continuous Development and Safety Assurance Pipeline for ML-Based Systems in the Railway Domain

연구 분야: Software Development

학회: International Conference on Computer Safety, Reliability, and Security

Automated Driving Systems (ADS) will operate in an open world. Since it is difficult to specify all possible situations in this open world a priori and the world will most likely change during the system’s lifecycle, it requires agile MLOps cycles, including testing & validation in the field. In this paper, we present how the safe MLOps process proposed in Zeller et al. [25] is realized in the safe.trAIn project using Git-centric methods. Thereby, appropriate tooling support is provided at the different stages of the safe MLOps process to enable continuous development and safety assurance of ML-based systems in the railway domain.