Human-machine function allocation method for aircraft cockpit based on interval 2-tuple linguistic information

Appropriate human-machine function allocation benefits the complement between pilots and automation, and makes the whole system more effective and reliable. Thus, the humanmachine function allocation method for aircraft cockpit based on interval 2-tuple linguistic information is proposed. The uncertain expanded weighted arithmetic averaging (UEWAA) operator and uncertain linguistic hybrid aggregation (ULHA) operator are extended into the interval 2-tuple linguistic environment based on uncertain linguistic multiple attribute decision making (ULMADM). And some new aggregation operators are developed, including the interval 2-tuple weighted average aggregation (IT-WAA) operator and the interval 2-tuple weighted hybrid aggregation (IT-WHA) operator. Uniformization of the multiple-granularity linguistic evaluation information is introduced to solve the problem of ULMADM not being able to deal with the multiple-granularity linguistic information from different decision-makers. Then the detailed steps of the proposed method are described. Finally, an illustrative example of the ground proximity warning system (GPWS) is provided to demonstrate the practicality, feasibility and superiority based on the comparison between the proposed method and ULMADM.