Among the motivations for the use of maritime surface autonomous ships (MASS) is the potential increase in safety when compared, to traditional ships - particularly regarding human error. However, the situation is not a direct reduction in human intervention, it is, just a transfer from the ship-based crew activities to the shore-based human operation in a shore-based control center (SCC). From the, current research trend, people pay more attention to the improvement of MASS's own intelligence level. The reliability of human, decision-making processing and operation have rarely been addressed. This paper explores how shore-based operator can be a key, factor for successful navigation tasks in future MASS operations. The Information, Decision, and Action in Crew context (IDAC), model is a cognitive process based human reliability analysis (HRA) that can model and assess the cognitive behavior of crews in SCC. The Maritime Accident Dynamic Simulator (MADS) is developed to provide a dynamic simulation environment for IDAC. The model, proposed in this paper is developed to simulate the task responses of SCC operator, during the risk detection and decision-making, process in daily navigation. Through the reasonable simplification of MASS system, the IDAC method decomposes the cognitive, behavior of SCC operators into three main processes: information processing, decision-making, and action execution. The simulated, physical situation of environment and mechanical conditions provides input information of the IDAC model, and the operator makes, relevant decisions and actions according to the real-time conditions. The simulation of ship collision avoidance scenarios between, MASSs reveal possible collision accidents of MASSs. This method can be used for modeling and quantitative analysis of human task, execution process in complex tasks under potential MASS application scenario.