Supporting Human-Automation Collaboration Through Dynamic Function Allocation

Abstract

Context-sensitive function allocation can take two forms: (a) ‘adaptable automation’, where changes in the allocation of functions are initiated by the user, or (b) ‘adaptive automation’, where the automation triggers changes. However, operational experience suggests that neither approach by itself is sufficient and appropriate. This paper describes a hybrid dynamic function allocation scheme, in which the system and the operator collaborate on selecting and activating appropriate automation levels. The default mode of the system is adaptive automation, but operators can override system selections when they feel the need and have the time to do so. The effectiveness of the hybrid system was compared to fixed function allocations, to an adaptive scheme and to adaptable function allocation in the context of simulated robotic arm control tasks. The hybrid system improved performance and reduced workload in routine scenarios. The system was also preferred over the fixed and adaptive approach by the operators. However, these benefits can be explained mainly by the excessive use of high levels of automation in this condition. The findings have implications on future designs of dynamic function allocation schemes in complex systems.