Flexibility in human-adaptable automation can provide important benefits, including improved situation awareness, more balanced mental workload and improved overall performance. This study develops a method enabling human-like, flexible supervisory control via delegation to automation. The authors review problems with static and adaptive (as opposed to "adaptable") automation; contrast these approaches with human-human task delegation, which can mitigate many of the problems; and revise the concept of a "level of automation" as a pattern of task-based roles and authorizations. It is argued that delegation requires a shared hierarchical task model between supervisor and subordinates, used to delegate tasks at various levels. On the basis of these analyses, the authors propose methods for supporting human-machine delegation interactions that parallel human-human delegation in important respects. An architecture for machine-based delegation systems is developed based on the metaphor of a sports team's "playbook." A prototype implementation of this architecture, along with an accompanying user interface and usage scenario, is described for mission planning for uninhabited air vehicles. This study suggests that delegation offers a viable method for flexible, multilevel human-automation interaction to enhance system performance while maintaining a manageable user workload.
Abstract