  A significant amount of work is invested in human-machine teaming (HMT)
across multiple fields. Accurately and effectively measuring system performance
of an HMT is crucial for moving the design of these systems forward. Metrics
are the enabling tools to devise a benchmark in any system and serve as an
evaluation platform for assessing the performance, along with the verification
and validation, of a system. Currently, there is no agreed-upon set of
benchmark metrics for developing HMT systems. Therefore, identification and
classification of common metrics are imperative to create a benchmark in the
HMT field. The key focus of this review is to conduct a detailed survey aimed
at identification of metrics employed in different segments of HMT and to
determine the common metrics that can be used in the future to benchmark HMTs.
We have organized this review as follows: identification of metrics used in
HMTs until now, and classification based on functionality and measuring
techniques. Additionally, we have also attempted to analyze all the identified
metrics in detail while classifying them as theoretical, applied, real-time,
non-real-time, measurable, and observable metrics. We conclude this review with
a detailed analysis of the identified common metrics along with their usage to
benchmark HMTs.
