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Publisher Copyright: © 2021 A new technique for the assessment of Team Situation Awareness (TSA) accuracy based upon post task Critical Decision Method structured interviews was developed and tested using 39 combat-ready F/A-18 pilots. Pilots undertook a number of simulated air combat scenarios, flying in flights of four aircraft against a formation of enemy aircraft. Results showed a strong curvilinear relationship where high TSA accuracy resulted in higher performance in some areas of air combat, measured with friendly losses and kills. There were diminishing returns in performance as TSA accuracy increased. This may explain why previous studies on air combat have found relatively weak relationships between situation awareness and performance where the relationship has been assumed to be linear.

This paper advances live (L), virtual (V), and constructive (C) simulation methodologies by introducing a new LVC simulation framework for the development of air combat tactics, techniques, and procedures (TTP). In the framework, TTP is developed iteratively in separate C-, V-, and L-simulation stages. This allows the utilization of the strengths of each simulation class while avoiding the challenges of pure LVC simulations. The C-stage provides the optimal TTP with respect to the probabilities of survival ( Ps) and kill ( Pk) of aircraft without considering the human–machine interaction (HMI). In the V-stage, the optimal TTP is modified by assessing its applicability with Pk and Ps, as well as HMI measures regarding pilots’ situation awareness, mental workload, and TTP adherence. In the L-stage, real aircraft are used to evaluate whether the developed TTP leads to acceptable Pk, Ps, and HMI measures in a real-life environment. The iterative nature of the framework enables that V- or L-stages can reveal flaws of the TTP and an inadequate TTP can be returned to the C- or V-stage for revision. This paper is Part 1 of a two-part study. Part 2 demonstrates the use of the framework with operationally used C- and V-simulators as well as real F/A-18C aircraft and pilots.

The purpose of this study was to demonstrate how the inclusion of a tactical task goal awareness measure complemented mental workload and performance measures in a simulated air combat mission. It was hypothesized that the evaluation of the tactical task goal awareness could provide additional information concerning the cognitive demands a pilot is exposed to during a complex air combat task. A test setting was developed to test this hypothesis in a virtual flight training device. To highlight the impact of task complexity, high performance aircraft pilots’ heart rate (HR), interbeat-interval (IBI), and performance in two simple flying tasks were first compared. Then, a similar comparison, complemented with the tactical task goal awareness measure, was made with two complex flying tasks. It was found that when the pilot's awareness of the tactical goals was low, a combination of low performance and low mental workload occurred. It was concluded that when the pilots’ performance is evaluated on a complex air combat task, the awareness of the tactical goals, performance, and mental workload should be studied together as the pilot's awareness can explain some of HR/IBI responses that could be otherwise misinterpreted. More generally, mental workload, performance, and task goal awareness should all be considered when the operator's performance in any complex human–machine system is assessed.

This paper advances the theoretical foundations and the methodology of spatial decision analysis in which multi-attribute consequences of decision alternatives vary over a spatial region. First, we introduce necessary and sufficient conditions for representing the decision maker’s preferences among such decision alternatives with an additive spatial value function. This new axiomatization allows for the representation of preferences when the spatial region consists of an infinite number of locations, which is often the case in practical applications. Moreover, we show that spatial value functions suggested in the existing literature can be interpreted as special cases of our additive spatial value function. Second, motivated by the high effort required to elicit preferences in spatial decision problems, we develop a method for utilizing the additive spatial value function with incomplete preference information about spatial weights describing the importance of locations and attribute weights. This method provides defensible decision recommendations through the use of dominance concepts and decision rules. The applicability of the developed value function and analysis method is illustrated with a real-life application in air defense planning.

Abstract. The aim of this study was to investigate the relationship between the flight-related core competencies for professional airline pilots and to structuralize them as components in a team performance framework. To achieve this, the core competency scores from a total of 2,560 OPC (Operator Proficiency Check) missions were analyzed. A principal component analysis (PCA) of pilots’ performance scores across the different competencies was conducted. Four principal components were extracted and a path analysis model was constructed on the basis of these factors. The path analysis utilizing the core competencies extracted adopted an input–process–output’ (IPO) model of team performance related directly to the activities on the flight deck. The results of the PCA and the path analysis strongly supported the proposed IPO model.

Games with incomplete preferences are normal-form games where the preferences of the players are defined as partial orders over the outcomes of the game. We define rationality in these games as follows. A rational player forms a set-valued belief of possible strategies selected by the opponent(s) and selects a strategy that is not dominated with respect to this belief. Here, we say a strategy is dominated with respect to the set-valued belief if the player has another strategy that would yield a better outcome according to the player's preference relation, no matter which strategy combination the opponent(s) play among those contained in the belief. We define rationalizable strategies as the logical implication of common knowledge of this rationality. We show that the sets of rationalizable strategies are the maximal mutually nondominated sets, i.e., the maximal sets that contain no dominated strategies with respect to each other. We show that no new rationalizable strategies appear when additional preference information is included. We consider multicriteria games as a special case of games with incomplete preferences and introduce a way of representing incomplete preference information in multicriteria games by sets of feasible weights of the criteria.

The utilization of dynamic Bayesian networks (DBNs) in simulation metamodeling enables the investigation of the time evolution of state variables of a simulation model. DBN metamodels have previously described the changes in the probability distribution of the simulation state by using a time slice structure in which the state variables are described at common time instants. In this paper, the novel approach to the determination of the time slice structure is introduced. It enables the selection of time instants of the DBN separately for each state variable. In this way, a more accurate metamodel representing multiple time scales of the variables is achieved. Furthermore, the construction is streamlined by presenting a dynamic programming algorithm for determining the key time instants for individual variables. The construction and use of the DBN metamodels are illustrated by an example problem dealing with the simulated operation of an air base.

Increased task demand will increase the pilot mental workload (PMWL). When PMWL is increased, mental overload may occur resulting in degraded performance. During pilots' instrument flight rules (IFR) proficiency test, PMWL is typically not measured. Therefore, little is known about workload during the proficiency test and pilots' potential to cope with higher task demands than those experienced during the test. In this study, fighter pilots' performance and PMWL was measured during a real IFR proficiency test in an F/A-18 simulator. PMWL was measured using heart rate (HR) and heart rate variation (HRV). Performance was rated using Finnish Air Force's official rating scales. Results indicated that HR and HRV differentiate varying task demands in situations where variations in performance are insignificant. It was concluded that during a proficiency test, PMWL should be measured together with the task performance measurement.

This paper introduces the use of Bayesian networks (BNs) as an exploratory metamodelling tool for supporting simulation studies conducted with stochastic simulation models containing multiple inputs and outputs. BN metamodels combine simulation data with available expert knowledge into a non-parametric description of the joint probability distribution of discrete random variables representing simulation inputs and outputs. The distributions of the inputs are determined based on expert knowledge and/or a real-world data source while the conditional distributions of the outputs are estimated from the simulation data. The exploratory use of the BN metamodels is an iterative process including the construction and validation of the BNs and allowing various analyses dealing with the dependencies among the inputs and the outputs, input uncertainty, and inverse reasoning. The results of these analyses are applied to guide and aid the utilization and interpretation of the simulation model under consideration. In addition, the analyses are used for studying the behaviour of the simulated system. The exploratory use is illustrated with an example involving a simulated queue.

Fighter pilots' heart rate (HR), heart rate variation (HRV) and performance during instrument approaches were examined. The subjects were required to fly instrument approaches in a high-fidelity simulator under various levels of task demand. The task demand was manipulated by increasing the load on the subjects by reducing the range at which they commenced the approach. HR and the time domain components of HRV were used as measures of pilot mental workload (PMWL). The findings of this study indicate that HR and HRV are sensitive to varying task demands. HR and HRV were able to distinguish the level of PMWL after which the subjects were no longer able to cope with the increasing task demands and their instrument landing system performance fell to a sub-standard level. The major finding was the HR/HRV's ability to differentiate the sub-standard performance approaches from the high-performance approaches. Practitioner Summary: This paper examined if HR and HRV were sensitive to varying task demands in a fighter aviation environment and if these measures were related to variations in pilot's performance.