Designing the interaction with Intelligent Decision Support Systems in Control Rooms: Challenges, Strategies, and Insights for Railway Applications

Control rooms are critical environments for managing complex socio-technical systems across sectors such as transportation and energy. The integration of AI into Decision Support Systems (DSS) introduces new design challenges, especially concerning explainability, trust, and situational awareness. While the back-end capabilities of these intelligent systems are rapidly evolving, ergonomic interaction design still lacks coherent frameworks and user-centered validation strategies. This study addresses these gaps through a systematic literature review focused on human– AI interaction in control room environments. The analysis highlights a predominant focus on situational awareness, with trust and explainability treated less consistently and often in isolation. Moreover, few studies adopt integrated design-evaluation approaches or actively involve end-users, revealing a disconnect between human- centered intentions and practical implementations. By identifying these trends and critical shortcomings, the paper contributes to mapping current research priorities and informing future design practices. Particular attention is drawn to the railway sector, which—despite its operational complexity—remains underrepresented in the literature. The results offer insights to foster more transparent, trustworthy, and ergonomically sound decision-support systems across safety-critical domains.