A Team Cognition Measurement Method for Single Pilot Operations Human-Machine System Design

Abstract

Team cognition is an important indicator to reflect the trend of single pilot operation (SPO) human-machine system team performance. How to measure team cognition to explore different function allocation decisions before the implementation of prototypes or simulators has become a significant step in the early SPO human-machine system design. Therefore, this article proposed a team cognition measurement method based on the social network analysis (SNA) method, namely cognitive social network analysis (CSNA). The CSNA method firstly identified the nodes, edge directions and channel resource values of each task; secondly calculated the cognitive demands of each task based on multiple resource theory; thirdly summed the cognitive demands of the same task to construct the association matrix; and finally calculated global and nodal network metrics. The results of the study showed that (1) the CSNA method could identify design flaws of the initial SPO human-machine system; (2) the CSNA method increased the ability to identify the changes in both the cognitive demands of tasks and the overall workloads of human agents compared to the SNA method; (3) the CSNA method could help researchers make reasonable design suggestions to improve the team performance of the redesigned SPO human-machine system. The above results not only verify the feasibility of the CSNA method, but also show that the CSNA method is superior to the current SNA method.