Adaptive HMI for Cyber-Physical Systems: Facilitating Multi-Level System Understanding for Rapid Response and Recovery

Abstract: In complex cyber-physical systems, especially those supporting high-stakes operational contexts, users face increasing demands to quickly comprehend and navigate intricate system data. As these systems grow in functionality, the volume and complexity of data presented on conventional interfaces can overwhelm users, particularly in scenarios requiring rapid response. During unexpected or unpredictable degradations of capability, users must transition swiftly from routine operations to diagnostic and triage actions, often under constrained timeframes. Conventional human-machine interfaces (HMIs) frequently lack the adaptive features needed to adjust not only the information presentation, but also the user interaction mechanisms based on the evolving system state. This limits user situational awareness and diagnostic efficiency. Additionally, traditional HMI designs do not adequately support multi-level system understanding, where both high-level and detailed abstractions of the system are often essential for making informed decisions under pressure. This gap between the increasing complexity of systems and the static nature of HMIs presents a critical challenge for maintaining operational resilience and effectiveness during degradation or recovery scenarios.To address these challenges, we are developing an adaptive human-machine interface (HMI) that leverages a dynamically reconfigurable display composed of digital OLED screens, each functioning as both a visual information source and an interactive control. Drawing on principles from cognitive systems engineering and ecological interface design (EID), the HMI is structured around an abstraction hierarchy, allowing users to view and interact with system states at multiple levels of abstraction, from high-level functional goals to detailed component states. This multi-layered approach enables users to access context-specific information that dynamically shifts in response to ongoing system data displayed on the primary monitor, aligning with the principles of cognitive compatibility. By presenting critical information through adaptive iconography and visual cues on the OLED screens, the system facilitates rapid perception of key operational states, significantly enhancing users’ capacity for efficient diagnostic reasoning during degraded operations.The interface’s adaptability is critical to helping users shift focus seamlessly between strategic and tactical tasks, a need particularly acute during triage and recovery phases when response time is crucial. By encoding higher-order functional information, the adaptive HMI minimizes cognitive load and reduces the risk of errors by guiding attention to actionable insights relevant to the current operational context. This design also supports “direct manipulation” of data at multiple levels, allowing users to interact with core system function information directly from the HMI, thus reinforcing the system’s transparency and intelligibility. These features make it possible to sustain a level of operational resilience even under conditions of reduced capability, as users can rapidly construct a situational model of the system’s behavior and prioritize actions accordingly. The approach’s alignment with ecological interface design principles fosters a robust user interface by emphasizing perceptual cues that map to the underlying system structure, supporting faster recognition and more effective response.This HMI prototype ultimately represents a significant advancement in facilitating cognitive work across varying levels of detail and complexity, enabling users to better understand, diagnose, and restore critical functionality in cyber-physical systems under high-stress, time-sensitive conditions.

Keywords: Human-Machine Interface, Ecological Interface Design, Abstraction Hierarchy, Adaptive Systems, Human Computer Interface (HCI), Cognitive Systems Engineering

DOI: 10.54941/ahfe1006239

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