Beyond Levels of Driving Automation: A Triadic Framework of Human-AI Collaboration in On-Road Mobility (2504.19120v1)

Abstract: The goal of the current study is to introduce a triadic human-AI collaboration framework for the automated vehicle domain. Previous classifications (e.g., SAE Levels of Automation) focus on defining automation levels based on who controls the vehicle. However, it remains unclear how human users and AI should collaborate in real-time, especially in dynamic driving contexts, where roles can shift frequently. To fill the gap, this study proposes a triadic human-AI collaboration framework with three AI roles (i.e., Advisor, Co-Pilot, and Guardian) that dynamically adapt to human needs. Overall, the study lays a foundation for developing adaptive, role-based human-AI collaboration strategies in automated vehicles.