Workload dynamics in safety-critical monitoring roles: evidence from the Belgian railway network

Increased mental workload leads to high stress levels or boredom during monitoring tasks, escalating the risk of human errors. Determining and quantifying an optimal mental workload level that maximizes operator performance presents a formidable challenge. Leveraging existing theoretical frameworks and literature on workload suboptimality, we constructed a quantitative System Dynamics model on workload and its impact on human error for safety-critical monitoring roles. This model is then rigorously tested and calibrated using real-world operational data from traffic controllers employed by the National Belgian Railway Infrastructure Company. The results point to (1) the support of operational data in the formulation of the feedback mechanism between an operator's workload and human error; (2) the quantification of overload and underload thresholds; (3) the dynamics associated with both thresholds, where increased fatigue levels lead to a shrinkage of the 'comfort zone'. The simulation model emerges as a potential approach for practitioners to assess the probability of human errors based on specific workload distributions. Beyond its immediate utility, the model also offers strategic insights for policy-making and schedule planning to enhance operator performance and ensure safety in socio-technical systems.