This paper presents a theoretical model of situation awareness based on its role in dynamic human decision making in a variety of domains. Situation awareness is presented as a predominant concern in system operation, based on a descriptive view of decision making. The relationship between situation awareness and numerous individual and environmental factors is explored. Among these factors, attention and working memory are presented as critical factors limiting operators from acquiring and interpreting information from the environment to form situation awareness, and mental models and goal-directed behavior are hypothesized as important mechanisms for overcoming these limits. The impact of design features, workload, stress, system complexity, and automation on operator situation awareness is addressed, and a taxonomy of errors in situation awareness is introduced, based on the model presented. The model is used to generate design implications for enhancing operator situation awareness and future directions for situation awareness research.

Methodologies for the empirical measurement of situation awareness are reviewed, including a discussion of the advantages and disadvantages of each method and the potential limitations of the measures from a theoretical and practical viewpoint. Two studies are presented that investigate questions of validity and intrusiveness regarding a query-based technique. This technique requires that a simulation of the operational tasks be momentarily interrupted in order to query operators on their situation awareness. The results of the two studies indicate that the query technique is not intrusive on normal subject behavior during the trial and does not suffer from limitations of human memory, which provides an indication of empirical validity. The results of other validity studies regarding the technique are discussed along with recommendations for its use in measuring situation awareness in varied settings.

Situation awareness (SA) is an important component of pilot/system performance in all types of aircraft. It is the role of the human factors engineer to develop aircraft cockpits which will enhance SA. Research in the area of situation awareness is is vitally needed if system designers are to meet the challenge of providing cockpits which enhance SA. This paper presents a discussion of the SA construct, important considerations facing designers of aircraft systems, and current research in the area of SA measurement.

The out-of-the-loop performance problem, a major potential consequence of automation, leaves operators of automated systems handicapped in their ability to take over manual operations in the event of automation failure. This is attributed to a possible loss of skills and of situation awareness (SA) arising from vigilance and complacency problems, a shift from active to passive information processing, and change in feedback provided to the operator. We studied the automation of a navigation task using an expert system and demonstrated that low SA corresponded with out-of-the-loop performance decrements in decision time following a failure of the expert system. Level of operator control in interacting with automation is a major factor in moderating this loss of SA. Results indicated that the shift from active to passive processing was most likely responsible for decreased SA under automated conditions.

Various levels of automation (LOA) designating the degree of human operator and computer control were explored within the context of a dynamic control task as a means of improving overall human/machine performance. Automated systems have traditionally been explored as binary function allocations; either the human or the machine is assigned to a given task. More recently, intermediary levels of automation have been discussed as a means of maintaining operator involvement in system performance, leading to improvements in situation awareness and reductions in out-of-the-loop performance problems. A LOA taxonomy applicable to a wide range of psychomotor and cognitive tasks is presented here. The taxonomy comprises various schemes of generic control system function allocations. The functions allocated to a human operator and/or computer included monitoring displays, generating processing options, selecting an`optimal' option and implementing that option. The impact of the LOA taxonomy was assessed within a dynamic and complex cognitive control task by measuring its eOE ect on human/system performance, situation awareness and workload. Thirty subjects performed simulation trials involving various levels of automation. Several automation failures occurred and out-of-the-loop performance decrements were assessed. Results suggest that, in terms of performance, human operators bene® t most from automation of the implementation portion of the task, but only under normal operating conditions; in contrast, removal of the operator from task implementation is detrimental to performance recovery if the automated system fails. Joint human/system option generation signi® cantly degraded performance in comparison to human or automated option generation alone. Lower operator workload and higher situation awareness were observed under automation of the decision making portion of the task (i.e. selection of options), although human/system performance was only slightly improved. The implications of these ® ndings for the design of automated systems are discussed.