Dynamic human error risk assessment of group decision-making in extreme cooperative scenario

For groups in extreme environments, their reliability requirements in complex operational systems are high due to isolation from society, physical constraints for extended periods of time, and exposure to significant hazards. This study attempts to solve the problem of dynamic quantitative risk analysis of decision-making process for extreme group during complex cooperative scenarios. Based on an extended IDA team cognitive model, typical failure modes and performance quantification mechanisms of team communication were analyzed. The performance curve was utilized to distinctively model the cognitive behaviors of operators within the team, driving the cognitive transmission paths of group decision-making in a hybrid event tree. Error calibration of human error due to time uncertainty was conducted. The steps and techniques for dynamic risk analysis of decision-making of extreme groups under complex, dynamic, and ambiguous scenarios were summarized. The proposed method was validated through simulation in a typical powered diving task of manned submarine.