A Human Cognitive Performance Measure Based on Available Options for Adaptive Aiding

Abstract

The concept of adaptive automation stipulates dynamically changing levels of automation as solution for the conflict between the advantages different static levels of automation offer. The use of a task performance measure to invoke adaptive automation enables adapting not only to the current situation but additionally to the specific needs of different operators. This paper presents an approach to measure the task performance by comparing the observed interaction behavior with the interaction options available during the interaction sequence. This takes account of the fact that the achievable result strongly depends on the current situation and the available interaction options. The presented approach is based on a Coloured-Petri-Net (CPN) simulation environment and generates action sequences in the Petri Nets state space, which represent the consequences of alternative options. Thereby, it becomes possible to evaluate operators’ actions taking into account the available options. This paper further discusses the advantages and disadvantages of the proposed approach regarding its application for adaptive automation. On the one hand the method is sensible to the environmental conditions and is able to measure the performance at any time. On the other hand a drawback of the method is its high computational demand, so that it has been used only for retrospective analyses up to now.