Evaluating Operator’s Cognitive Workload in Six-Dimensional Tracking and Control Task within an Integrated Cognitive Architecture

Abstract

Six-dimensional tracking and control task within an Integrated Cognitive Architecture, as a makeup for automated Six-dimensional tracking and control task default. is a common yet highly complex space operation, challenging the human workload. For space exploration system safety, workload is a critical factor in task design and implementation. This research integrates two cognitive architectures: Queuing Network QN & Adaptive Control of Thought-Rational ACT-R to develop a rigorous computational model for Six-dimensional tracking and control task cognition process. ACT-R represents the human mind as a production rule system. Experiments are set up to build Six-dimensional tracking and control task cognition model and afterwards to validate feasibility of the proposed integrated cognition architecture. Ten subjects of similar training level are chosen to finish manual Six-dimensional tracking and control task with three task difficulty level: one only with displacement margin, one only with posture margin and one with displacement and posture margin. Cognition task analysis is firstly conducted on task performance of subjects. Cognition model of manual Six-dimensional tracking and control task is then built up based on the proposed integration architecture. The proposed integration model developed in the ACTR-QN describes component processes of tracking, decision making and controlling in a 3D environment by ACT-R production rules within QN network. Workload index for each cognition module is calculated based on sector utility throughout the whole task. Human results are compared with the modeled results in the dimension of task time and displacement/posture control trajectory deviation. Workload index is calculated based on the percentage of each module in the time dimension.