Evaluating algorithmic techniques in supporting situation awareness

被引:17
|
作者
Salerno, J [1 ]
Blasch, E [1 ]
Hinman, M [1 ]
Boulware, D [1 ]
机构
[1] USAF, AFRL, IFEA, Res Lab, Rome, NY 13440 USA
关键词
situation awareness; metrics; evaluation; precision; recall; misassignment rate; evidence recall; cost utility; timeliness; data to information ratio;
D O I
10.1117/12.603825
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
How well does an algorithm support its purpose and user base? Has automation provided the user with the ability to augment their production, quality or responsiveness? In a number of systems today these questions can be answered by either Measures of Performance (MOP) or Measures of Effectiveness (MOE). However, the fusion community has not yet developed sufficient measures and has only recently devoted a concerted effort to address this deficiency. In this paper, we will summarize work in metrics for the lower levels of fusion (object ID, tracking, etc) and discuss whether these same metrics still apply to the higher levels (Situation Awareness), or if other approaches are necessary. We conclude this paper with a set of future activities and direction.
引用
收藏
页码:96 / 104
页数:9
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