Modeling human behavior in manual control Rendezvous and Docking task

Abstract

Manual control rendezvous and docking (RVD) with human participation can be used when autonomous RVD is invalid under uncertain environment. Because of the particularity and complexity of the RVD task, it is necessary to understand human cognitive processes when evaluating human performance. A modeling approach, focusing on the information processing underlying the decisions process, is proposed to achieve real-time visualization of information processing and to generate human-like behavior of manual control RVD in this paper. It is implemented by combining the symbolic knowledge representations with queuing network mechanism. This computational model here can be used for describing and explaining how human cognition works. Furthermore, a quantitative validation of the model is conducted by comparing the performance results of the model with the results of people doing the same tasks, which reflects that this model can be applied as "replacements" for human participants to evaluate their cognition and performance in manual control RVD task.