Modeling Human and Organizational Behavior Application to Military Simulations (1998) / Chapter Skim
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7 Situation Awareness
7 Situation Awareness
Pages 172-202
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The military uses the term situation awareness to refer to the static spatial awareness of friendly and enemy troop positions. We broaden this defini 172
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We should also note that considerable research remains to be done on defining, understanding, and quantifying situation awareness as necessary precursors to the eventual development of valid descriptive process models that accurately and reliably model human behavior in this arena. Because of the early stage of the research on situation awareness, much of the discussion that follows focuses on potential prescriptive (as opposed to descriptive)
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· Perception of the elements in the environment within a volume of time and space · Comprehension of their meaning · Projection of their status in the near future · The ability to envision the current and near-term disposition of both friendly and enemy forces · Where: knowledge of the spatial relationships among aircraft and other objects · What: knowledge of the presence of threats and their objectives and of ownship system state · Who: knowledge of who is in charge the operator or an automated system · When: knowledge of the evolution of events over time · Estimate of the purpose of activities in the observed situation · Understanding of the roles of participants in these activities · Inference about completed or ongoing activities that cannot be directly observed · Inference about future activities · The knowledge that results when attention is allocated to a zone of interest at a level of abstraction · Just a label for a variety of cognitive processing activities that are critical to dyamic, event-driven, and multitask fields of practice · Continuous extraction of environmental information, integration of this knowledge to form a coherent mental picture, and the use of that picture in directing further perception and anticipating future events . · Spatial awareness · Mission/goal awareness System awareness · Resource awareness · Crew awareness .
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A number of studies of human behavior in low-tempo tactical planning have demonstrated how decision biases and poor situation awareness contribute to poor planning (Tolcott et al., 1989; Fallesen and Michel, 1991; Serfaty et al., 1991; Lussier et al., 1992; Fallesen, 1993; Deckert et al., 1994~. Certain types of failures are common, resulting in inadequate development and selection of courses of action.
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MODELS OF SITUATION AWARENESS A variety of situation awareness models have been hypothesized and developed by psychologists and human factors researchers, primarily through empirical studies in the field, but increasingly with computational modeling tools. Because of the critical role of situation awareness in air combat, the U.S.
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. Descriptive Situation Awareness Models Most developed situation awareness models are descriptive.
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Prescriptive Situation Awareness Models In contrast to the situation with descriptive models, few prescriptive models of situation awareness have been proposed or developed. Early attempts used production rules (Baron et al., 1980; Milgram et al., 1984~.
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. In the SUTT human behavior representation, situation awareness is modeled as primarily a low-level collection of "events" (identified and located entities)
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to the modeling of human behavior in the tactical air domain. Initial efforts led to a limited-scope demonstration of feasibility, fixed-wing attack (FWA)
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(1996, 1997) have used belief networks to develop prescriptive situation awareness models for two widely different domains: counter-air operations and nuclear power plant diagnostic monitoring.
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ENABLING TECHNOLOGIES FOR IMPLEMENTATION OF SITUATION AWARENESS MODELS A number of approaches can be taken to implement situation awareness models, from generic inferencing approaches (e.g., abductive reasoning, see, for example, Josephson and Josephson, 1994) to specific computational architectures (e.g., blackboard architectures, Hayes-Roth, 1985~.
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Expert Systems5 An early focus of expert system development was on applications involving inferencing or diagnosis from a set of observed facts to arrive at a more general assessment of the situation that concisely "explains" those observed facts. Consequently, there has been interest in using expert systems to implement situation awareness models.
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Many practical expert systems allow for a combination of both strategies (Russell and Norvig, 1995; Ng and Abramson, 1990~. The majority of current military human behavior representations reviewed for this study implicitly incorporate an expert-system-based approach to situation awareness modeling.
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adaptation rules. A major motivation for using a case-based reasoning approach to the modeling of situation assessment, and human decision making in general, is that explicit reference to individual previously experienced instances or cases is often a central feature of human problem solving.
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Whether effective case-based reasoning models of situation awareness will be developed for future human behavior representations is still an open research question, but clearly one worth pursuing. Bayesian Belief Networks9 Bayesian belief networks (also called belief networks and Bayesian networks)
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belief networks and how they might be used to model the military situation assessment process. A belief network is a graphical representational formalism for reasoning under uncertainty (Pearl, 1988; Lauritzen and Spiegelhalter,1988~.
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algorithm is used to compute the belief values given the evidence. To illustrate how a belief network model could be used to model the situation assessment of an S-2 staff, Figure 7.3 shows a hypothetical battle scenario in which an enemy motorized rifle division will invade its neighbor to the west.
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These reports will be processed by the S-2 staff, who will incrementally adjust degrees of belief in the various hypotheses about enemy positions, dispositions, and so on represented in the system. Figure 7.4 depicts a simple belief network model supporting blue situation awareness of red activity that might take place under this scenario.
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. The conditional probability table of the figure essentially encodes the doctrinal knowledge that, given that a Russian motorized rifle division (MRD)
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A number of modeling efforts have also been conducted by Zacharias and colleagues to develop belief network-based situation awareness models of Air Force decision makers. Zacharias et al.
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Obviously the specific details of the model implementation will need to be taken into account before a fair assessment can be made as to the pros and cons of enhancement versus replacement. RELATIONSHIPS TO OTHER MODELS This section describes how situation awareness models relate to other models comprising a human behavior representation.
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Otherwise, there will be a tendency for the human behavior representation to be omniscient, so that downstream situation assessment processing is likely to be error free and nonrepresentative of actual human assessment behavior. By explicitly modeling perceptual limitations in this fashion, we will be more likely to capture inappropriate assessments of the situation that occur with a "correct" assessment strategy, but an "incorrect" perceptual knowledge base.
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Most of the work in this area has been done in the visual modality, and an extensive literature exists. The following subsections briefly describe four visual perception models that offer potential for driving a situation awareness model and accounting for human perceptual capabilities and limitations in a more realistic fashion.
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The Georgia Tech Vision model also provides a highly detailed representation of the earliest physiological functions of the human visual system, such as dynamics of luminance adaptation due to receptor pigment bleaching, pupil dilation, and receptor thresholds. It is not clear whether this level of detail is appropriate for a model that is ultimately concerned with P`3 and Pfa, especially given the associated computational complexity: a single input image generates up to 144 intermediate equal-size images.
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RED, in which action selection immediately follows situation recognition. The majority of human behavior representations reviewed for this study model this process using a simple production rule of the form: IF (Sj is true)
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Both of these can be learned if sufficient training cases are presented to the belief network. To learn the conditional probability tables for a fixed structure, one keeps track of the frequencies with which the values of a given variable and those of its parents occur across all samples observed up to the current time (Koller and Breese, 13However, it should be recognized that this ease of learning comes at the cost of increased retrieval time as experience grows (to be contrasted with observed human behavior)
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The discussion here focuses on how a situation awareness model would support a planning model during both initial planning and plan monitoring. During the initial planning stage there is a need to specify three key categories of information: · Desired (foals In standard planning jargon, this is the desired goal state.
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As part of this effort, we reviewed three specific technologies that appear to have significant potential in situation awareness model development: expert systems, case-based reasoning, and belief networks. We noted in this review that early situation awareness models, and a surprising number of current DoD human behavior representations, rely on an expert systems approach (or, closely related, decision tables)
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· In future perceptual modeling efforts undertaken for the development of military human behavior representations, include a review of the following: Informational modeling approaches in the existing human operator litera ture. Visual modeling approaches to object detection/recognition supported extensively by a number of DoD research laboratories.
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· For situation awareness models based on belief networks, consider using an embeddable belief network engine. As with model development based on expert systems, maintain an audit trail of the way knowledge information sources contributed to the specification of belief network topology and parameter values.
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For models based on belief networks, explore new learning techniques now being proposed that are based on sampled statistics derived from observed situations. · Explore means of incorporating the effects of stressors/moderators in situation awareness models.
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