Coordinating Stakeholders in the Consideration of Performance Indicators and Respective Interface Requirements for Automated Vehicles

2026-03-19

AI Summary

This study addresses the challenges faced by SAE Level 4 autonomous driving systems in handling internal and external disturbances and faults, which are often exacerbated by a lack of stakeholder consensus on performance metrics and interface requirements, leading to non-traceable architectural decisions and inefficient communication. To overcome these issues, this work proposes a process-oriented engineering methodology that employs structured steps to harmonize multi-stakeholder requirements, explicitly define the performance metrics and interface specifications necessary for self-awareness and self-adaptation capabilities, and systematically integrate traceability and knowledge transfer mechanisms into the architecture design process. Validated within the autotech.agil project, the approach significantly enhances requirement consistency, decision transparency, and collaboration efficiency, while yielding key practical insights and directions for future improvement.

Technology Category

• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Multiagent Systems: Mechanism Design
• Search and Optimization: Metareasoning and Metaheuristics

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

This paper presents a process for coordinating stakeholders in their consideration of performance indicators and respective interface requirements for automated vehicles. These performance indicators are obtained and processed based on the system's self-perception and enable the realization of self-aware and self-adaptive vehicles. This is necessary to allow SAE Level 4 vehicles to handle external disturbances as well as internal degradations and failures at runtime. Without such a systematic process for stakeholder coordination, architectural decisions on realizing self-perception become untraceable and effective communication between stakeholders may be compromised. Our process-oriented approach includes necessary ingredients, steps, and artifacts that explicitly address stakeholder communication, traceability, and knowledge transfer through clear documentation. Our approach is based on the experience gained from applying the process in the autotech.agil project, from which we further present lessons learned, identified gaps, and steps for future work.

Problem

• stakeholder coordination
• performance indicators
• automated vehicles
• interface requirements
• self-perception

Innovation

• stakeholder coordination
• performance indicators
• self-perception
• automated vehicles
• interface requirements