Assessing expertise using eye tracking in a Virtual Reality flight simulation

Objective: The aim of this work was to examine the fidelity and validity of an aviation simulation using eye tracking. Background: Commercial head-mounted virtual reality (VR) systems offer a convenient and cost-effective alternative to existing aviation simulation (e.g., for refresher exercises). We performed pre-implementation testing of a novel aviation simulation, designed for head-mounted VR, to determine its fidelity and validity as a training device. Method: Eighteen airline pilots, with varying levels of flight experience, completed a sequence of training ‘flows’. Self-reported measures of presence and workload and users’ perceptions of fidelity were taken. Pilots’ eye movements and performance were recorded to determine whether more experienced pilots showed distinct performance and eye gaze profiles in the simulation, as they would in the real-world. Results: Real-world expertise correlated with eye gaze patterns characterised by fewer, but longer, fixations and a scan path that was more structured and less random. Multidimensional scaling analyses also indicated differential clustering of strategies in more versus less experienced pilots. Subjective ratings of performance, however, showed little relationship with real-world expertise or eye movements. Conclusion: We adopted an evidence-based approach to assessing the fidelity and validity of a VR flight training tool. Pilot reports indicated the simulation was realistic and potentially useful for training, while direct measurement of eye movements was useful for establishing construct validity and psychological fidelity of the simulation.

Stabilization of unmanned aerial vehicle on trajectory in high wind conditions

Stationary proportional control laws have been synthesized to ensure stable motion of an unmanned aerial vehicle along a trajectory under the action of a storm wind. We give the values of the regulator coefficients for all sections of the trajectory from the starting point to the landing. Shown are the realizations of wind disturbances and the parameters of the controlled motion of the aircraft under their action. We consider the accuracy of altitude control and the error of the coordinates of the landing site. The control laws use the values of constant coefficients obtained at five points of the trajectory. Three points are used for the climb phase and one for level flight and one for descent. We took into account the wind speed as the sum of the three-dimensional turbulent component, the average horizontal component, considering the vertical shear, and discrete vertical gusts. The parameters of the Dryden shaping filters, as well as the vertical shear, are calculated for an average wind speed at a height of 6 m equal to 23.15 m / s. The speed of discrete upward gusts is 40 m/s, and downward -25 m / s. In such conditions, the unmanned aerial vehicle successfully passes the specified trajectory from the launch to the landing. For thirty realizations of flight simulation, the standard deviation of the landing site error from the wind acting was calculated.

Formation control method based on artificial potential fields for aircraft flight simulation

As simulation becomes more present in the military context for variate purposes, the need for accurate behaviors is of paramount importance. In the air domain, a noteworthy behavior relates to how a group of aircraft moves in a coordinated way. This can be defined as formation flying, which, combined with a move-to-goal behavior, is the focus of this work. The objective of the formation control problem considered is to ensure that simulated aircraft fly autonomously, seeking a formation, while moving toward a goal waypoint. For that, we propose the use of artificial potential fields, which reduce the complexities that implementing a complete cognition model could pose. These fields define forces that control the movement of the entities into formation and to the prescribed waypoint. Our formation control approach is parameterizable, allowing modifications that translate how the aircraft prioritize its sub-behaviors. Instead of defining this prioritization on an empirical basis, we elaborate metrics to evaluate the chosen parameters. From these metrics, we use an optimization methodology to find the best parameter values for a set of scenarios. Thus, our main contribution is bringing together artificial potential fields and simulation optimization to achieve more robust results for simulated military aircraft to fly in formation. We use a large set of scenarios for the optimization process, which evaluates its objective function through the simulations. The results show that the use of the proposed approach may generate gains of up to 27% if compared to arbitrarily selected parameters, with respect to one of the metrics adopted. In addition, we were able to observe that, for the scenarios considered, the presence of a formation leader was an obstacle to achieving the best results, demonstrating that our approach may lead to conclusions with direct operational impacts.

The systematic evaluation of an embodied control interface for virtual reality

Embodied interfaces are promising for virtual reality (VR) because they can improve immersion and reduce simulator sickness compared to more traditional handheld interfaces (e.g., gamepads). We present a novel embodied interface called the Limbic Chair. The chair is composed of two separate shells that allow the user’s legs to move independently while sitting. We demonstrate the suitability of the Limbic Chair in two VR scenarios: city navigation and flight simulation. We compare the Limbic Chair to a gamepad using performance measures (i.e., time and accuracy), head movements, body sway, and standard questionnaires for measuring presence, usability, workload, and simulator sickness. In the city navigation scenario, the gamepad was associated with better presence, usability, and workload scores. In the flight simulation scenario, the chair was associated with less body sway (i.e., less simulator sickness) and fewer head movements but also slower performance and higher workload. In all other comparisons, the Limbic Chair and gamepad were similar, showing the promise of the Chair for replacing some control functions traditionally executed using handheld devices.

On Cognitive Searching Optimization in Semi-Markov Jump Decision Using Multistep Transition and Mental Rehearsal

Cognitive searching optimization is a subconscious mental phenomenon in decision making. Aroused by exploiting accessible human action, alleviating inefficient decision and shrinking searching space remain challenges for optimizing the solution space. Multiple decision estimation and the jumpy decision transition interval are two of the cross-impact factors resulting in variation of decision paths. To optimize the searching process of decision solution space, we propose a semi-Markov jump cognitive decision method in which a searching contraction index bridges correlation from the time dimension and depth dimension. With the change state and transition interval, the semi-Markov property can obtain the action by limiting the decision solution to the specified range. From the decision depth, bootstrap re-sampling utilizes mental rehearsal iteration to update the transition probability. In addition, dynamical decision boundary by the interaction process limits the admissible decisions. Through the flight simulation, we show that proposed index and reward vary with the transition decision steps and mental rehearsal frequencies. In conclusion, this decision-making method integrates the multistep transition and mental rehearsal on semi-Markov jump decision process, opening a route to the multiple dimension optimization of cognitive interaction.