Stakeholder-Oriented Explainability Requirements for Advanced Driver Assistance Systems and Automated Driving Systems: A Structured Analysis

The development and validation of advanced driver-assistance systems (ADAS) and automated driving systems (ADS) are shifting from traditional linear V-model processes toward more iterative engineering cycles. Despite faster iteration, these safety-critical systems remain subject to stringent German and European regulations. Standards and guidance, including UNECE UN Regulation No. 157 and ISO/TR 4804, emphasize traceability, transparency, and explainability throughout development and validation. Nevertheless, as ADAS/ADS are developed and validated in faster, more iterative release cycles, additional stakeholders become involved and new explainability requirements emerge. These requirements vary between stakeholders and across development, validation, and post-market deployment phases, yet they are not systematically captured in the current state of research and practice. Therefore, to ensure that explainability supports rapid iteration, it is essential to identify relevant stakeholders and specify their explainability needs. While IEEE Std 7001-2021 provides a broad foundation for transparency in autonomous systems, its generic nature does not address the domain-specific complexities of ADAS/ADS. Furthermore, a conceptual gap remains between general transparency principles and explainability requirements in automotive development and validation. Building on IEEE Std 7001-2021, this paper first proposes a stakeholder-oriented classification method for automated driving use cases and contexts. It then defines the relevant stakeholders within this context and conducts a comprehensive, structured analysis of their explainability requirements. This analysis specifically focuses on the motivations for requiring explainability and the desired forms of explanation. Based on this analysis, stakeholder explainability needs are assessed and rated. Finally, we validate the results via semi-structured interviews with experts from both industry and academia, highlighting implications for integrating stakeholder-specific explainability into iterative ADS development and validation. The results of the paper provide a structured baseline for stakeholder-centric explainability requirements in ADAS/ADS.