Collaborating with a squad of Unmanned Aerial Vehicles (UAVs) is challenging for a human operator in a cooperative surveillance task. In this paper, we propose a cognitive model that can dynamically adjust the Levels of Autonomy (LOA) of the human-UAVs team according to the changes in task complexity and human cognitive states. Specifically, we use the Situated Fuzzy Cog-nitive Map (SiFCM) to model the relations among tasks, situations, human states and LOA. A recurrent structure has been used to learn the strategy of adjusting the LOA, while the collaboration task is separated into a perception routine and a control routine. Experiment results have shown that the workload of the human operator is well balanced with the task efficiency.