When Driving Automation Exceeds Human Ability: Authoritative Control Interventions and their Implications for Human-Machine Interaction

Advances in artificial intelligence and driving automation are fostering a paradigm shift in which technical systems exhibit cognitive and operational capabilities that surpass human performance. These developments have prompted proposals to grant automated systems greater control and authority, including allowing the automation to act authoritatively, fully blocking or taking away control from human users. While such delegation may promise improvements in safety and efficiency, it also carries the risk of disempowering humans if not carefully managed. This tension underscores a central challenge for human–machine interaction (HMI) design: maintaining operator agency and trust when interacting with automated systems that demonstrate ability beyond that of humans. The concept of Control Management, originating from aerospace, offers a pathway for balancing authority between human and automation by defining system policies that guide its architecture, mechanisms, and HMI design. In this conceptual work, we examine the theoretical foundations of human-automation collaboration and describe emerging challenges for driver interaction with authoritative automation. This work contributes: (1) a conceptual classification of authoritative control interventions across automation levels and control authority transition types, (2) Control Management-informed HMI guidelines spanning Avoid, Alert, Inform, Recover, and Return intervention states, (3) ethical implications for preserving driver agency, and (4) research directions for system development, policymakers, and HMI designers.