Developing an agent-based hierarchical modeling approach to assess human performance of infrastructure systems

• An agent-based hierarchical modeling for human performance is proposed.
• It focuses on the assessment of operator performance in infrastructure systems.
• CREAM and fuzzy sets model the human cognition component.
• Feasibility of the proposed approach is verified on electric power supply system.
• The approach bridges gap between advanced modeling and human performance assessment.

During the last decade, research works related to modeling and simulation of infrastructure systems have primarily focused on the performance of their technical factors, almost ignoring the importance of non-technical factors of these systems, e.g., human operators, consumers. In contrast, the human operator of infrastructure systems has become an essential part in daily operation and in ensuring the security and reliability of the system. In some of the most significant technological incidents of the past century, human error has played a major role. Therefore, developing a modeling approach that is capable of assessing the human performance in a comprehensive way has become crucial. In this paper, an agent-based hierarchical modeling approach is proposed, which aims at the explicit modeling of the impacts of human performance on the operation of infrastructure systems. Within this approach, the cognition component plays a major role. For this purpose, an analytical method based on the Cognitive Reliability Error Analysis Method (CREAM) is developed using a knowledge-based approach. The proposed modeling approach is a pilot work exploring possibilities of simulating performance of human factors in infrastructure systems. The applicability of this modeling approach is demonstrated by a validation experiment using the electric power supply system as an exemplary system.