Entropy-Enhanced EAST to Assess Distributed Situational Awareness in Human-Machine Interfaces

Abstract

In complex sociotechnical systems, situational awareness (SA) emerges not from individuals alone but from the shared understanding distributed across human agents, automated subsystems, and information artefacts. Effective coordination therefore depends on distributed situational awareness (DSA), with human–machine interfaces (HMIs) playing a central role. However, traditional HMI evaluations often overlook how DSA is structured by agents' roles, task interdependencies, and communication networks. This paper introduces a method that extends the Event Analysis of Systemic Teamwork (EAST) with an entropy measure, derived from Hick's Law, to quantify informational complexity. The integration provides a systematic means of assessing whether information distribution supports task demands and agent capacity. A walkthrough application illustrates how the method detects DSA misalignments and guides reconfiguration by redistributing information to balance entropy. Results show that entropy-enhanced EAST highlights critical nodes and offers deeper insight into DSA dynamics. The findings also reveal how interface design choices -such as deliberately increasing complexity to enforce communication—shape the distribution of awareness across agents.