SDP-based machine learning for flight cadets’ situational awareness

The purpose of the present study was to evaluate the effectiveness of subjective and objective probe questions in predicting situation awareness as measured by the Situation Awareness Rating Technique (SART). The data for this evaluation were taken from a previous investigation in which instrument-rated pilots flew automated ILS approaches into the Dallas-Fort Worth (DFW) Airport while monitoring the status of patrol vehicles proximal to their approach path. At three points during a simulation run, pilots were administered a questionnaire containing seven questions designed to probe situation awareness. At the end of the run, SART was administered. We found that certain probe questions can predict SART scores. However, the usefulness of these probes requires that the questions be designed in conjunction with scenario development to ensure that operationally critical variables are being probed, and that sufficient variability in the responses allow assessments of relations with sufficient statistical power.

Assessment of Radiation Therapy Technologists’ Workload and Situation Awareness: Monitoring 2 Versus 3 Collocated Display Monitors

Nuclear power plant diagnostic tasks impose high demands on operators’ situation awareness (SA) due to high time pressure and complex information integration. Based on information flow theory, this study first proposes information flow rate (bits/s) as an objective predictor of SA for nuclear diagnostic tasks, validating its effectiveness through simulations of steam generator tube rupture (SGTR) and small-break loss-of-coolant accident (SBLOCA) scenarios. Twenty-two participants (skilled and less-skilled groups) were recruited, using SART scores and eye tracking (gaze entropy) to measure SA and analyze the impact of information flow rate. Results demonstrated a significantly negative correlation between information flow rate and Situation Awareness Rating Technique (SART) scores ( r = − 0.8837 , p < 0.01), where high flow rates reduce SA. Skilled operators focused more on critical signals than less-skilled counterparts ( p = 0.16). SART scores were highly correlated with gaze entropy ( r = − 0.91 , p < 0.001 ), and SGTR tasks were more complex than SBLOCA (SART: 21.05 versus 19.02 , p = 0.003 ). Information flow rate effectively predicts SA levels, providing a quantitative basis for optimizing emergency operating procedures and operator training (e.g. high flow rate simulation exercises).

The risk of major occupational accidents involving tripping hazards is commonly underestimated with a large number of studies having been conducted to better understand variables that affect situation awareness: the ability to detect, perceive, and comprehend constantly evolving surroundings. An important property that affects situation awareness is the limited capacity of the attentional system. To maintain situation awareness while exposed to tripping hazards, a worker needs to obtain feedforward information about hazards, detect immediate tripping hazards, and visually scan surroundings for any potential environmental hazards. Despite the importance of situation awareness, its relationship with attention remains unknown in the construction industry. To fill this theoretical knowledge gap, this study examines differences in attentional allocation between workers with low and high situation awareness levels while exposed to tripping hazards in a real construction site. Participants were exposed to tripping hazards on a real jobsite while walking along a path in the presence of other workers. Situation awareness was measured using the situation awareness rating technique, and subjects’ eye movements were tracked as direct measures of attention via a wearable mobile eye tracker. Investigating the attentional distribution of subjects by examining fixation-count heat maps and scan paths revealed that as workers with higher situation awareness walked, they periodically looked down and scanned ahead to remain fully aware of the environment and its associated hazards. Furthermore, this study quantitatively compared the differences between the eye-tracking metrics of worker with different situation awareness levels (low versus high) using permutation simulation. The results of the statistical analysis indicate that subjects did not allocate their attention equally to all hazardous areas of interest, and these differences in attentional distribution were modulated by the workers’ level of situation awareness. This study advances theory by presenting one of the first attempts to use mobile eye-tracking technology to examine the role of cognitive processes (i.e., attention) in human error (i.e., failure to identify a hazard) and occupational accidents.

A review of the effects of head-worn displays on teamwork for emergency response

The paper describes flight trials performed in Reno, NV. Flight trial were conducted with a Cheyenne 1 from Marinvent. Twelve pilots flew the Cheyenne in seventy-two approaches to the Reno airfield. All pilots flew completely andomized settings. Three different settings (standard displays, 2D moving map, and 2D/3D moving map) were evaluated. They included seamless evaluation for STAR, approach, and taxi operations. The flight trial goal was to evaluate the objective performance of pilots compared among the different settings. As dependent variables, positional and time accuracy were measured. Analysis was conducted by an ANOVA test. In parallel, all pilots answered subjective Cooper-Harper, situation awareness rating technique (SART), situational awareness probe (SAP), and questionnaires.This article describes the human factor analysis from flight trials performed in Reno, NV. Flight trials were conducted with a Cheyenne 1 from Marinvent. Thirteen pilots flew the Cheyenne in seventy-two approaches to the Reno airfield. All pilots flew completely randomized settings. Three different display configurations: Elec. Flight Information System (EFIS), EFIS and 2D moving map, and 3D SVS Primary Flight Display (PFD) and 2D moving map were evaluated. They included normal/abnormal procedure evaluation for: Steep turns and reversals, Unusual attitude recovery, Radar vector guidance towards terrain, Non-precision approaches, En-route alternate for non-IFR rated pilots encountering IMC, and Taxiing on complex taxi-routes. The flight trial goal was to evaluate the objective performance of pilots for the different display configurations. As dependent variables, positional and time data were measured. Analysis was performed by an ANOVA test. In parallel, all pilots answered subjective NASA Task Load Index, Cooper-Harper, Situation Awareness Rating Technique (SART), and questionnaires. The result shows that pilots flying 2D/3D SVS perform no worse than pilots with conventional systems. In addition, 3D SVS flying pilots have significantly better terrain awareness, more stable 180° deg turns, and enhanced positional awareness while taxiing on the ground. Finally, even non-IFR rated pilots are able to fly non-precision approaches under IMC with a 3D SVS.

The aim of this study was to examine whether the Situation Present Assessment Method (SPAM) and the Situation Awareness Global Assessment Technique (SAGAT) predict incremental variance in performance on a simulated submarine track management task and to measure the potential disruptive effect of these situation awareness (SA) measures. Submarine track managers use various displays to localize and track contacts detected by own-ship sensors. The measurement of SA is crucial for designing effective submarine display interfaces and training programs. Participants monitored a tactical display and sonar bearing-history display to track the cumulative behaviors of contacts in relationship to own-ship position and landmarks. SPAM (or SAGAT) and the Air Traffic Workload Input Technique (ATWIT) were administered during each scenario, and the NASA Task Load Index (NASA-TLX) and Situation Awareness Rating Technique were administered postscenario. SPAM and SAGAT predicted variance in performance after controlling for subjective measures of SA and workload, and SA for past information was a stronger predictor than SA for current/future information. The NASA-TLX predicted performance on some tasks. Only SAGAT predicted variance in performance on all three tasks but marginally increased subjective workload. SPAM, SAGAT, and the NASA-TLX can predict unique variance in submarine track management performance. SAGAT marginally increased subjective workload, but this increase did not lead to any performance decrement. Defense researchers have identified SPAM as an alternative to SAGAT because it would not require field exercises involving submarines to be paused. SPAM was not disruptive, but it is potentially problematic that SPAM did not predict variance in all three performance tasks.

External Human–Machine Interfaces (eHMIs) enhance pedestrian safety in interactions with autonomous vehicles (AVs) by signaling crossing risk based on time-to-arrival (TTA), categorized as low, medium, or high. This study compared five eHMI configurations (single-level low, medium, high; two-level low-medium, medium-high) against a three-level (low-medium-high) configuration to assess their impact on pedestrians’ crossing decisions, mental workload (MW), and situation awareness (SA) in vehicle platoon scenarios under full and partial eHMI penetration. In a video-based experiment with 24 participants, crossing decisions were evaluated via temporal gap selection, MW via P300 event-related potentials in an auditory oddball task, and SA via the Situation Awareness Rating Technique. The three-level configuration outperformed single-level medium, single-level high, two-level low-medium, and two-level medium-high in gap acceptance, promoting safer decisions by rejecting smaller gaps and accepting larger ones, and exhibited lower MW than the two-level medium-high configuration under partial penetration. No SA differences were observed. Although the three-level configuration was generally appreciated, future research should optimize presentation to mitigate issues from rapid signal changes. Notably, the single-level low configuration showed comparable performance, suggesting a simpler alternative for real-world eHMI deployment.

This paper introduces a virtual reality (VR)-based unmanned aerial vehicle (UAV) simulator designed to support immersive training and early-stage human factors evaluations in rescue and emergency mission contexts. The system simulates a leader-follower UAV configuration, where a human operator controls a lead drone through a VR headset and joystick, while autonomous drones maintain any geometric formations using onboard sensing and dynamic obstacle avoidance [1]. This swarm-based coordination reflects real-world search and rescue scenarios, where rapid decision-making, spatial awareness, and teamwork are essential.The simulator is developed with a focus on human-in-the-loop design, providing an immersive teleoperation experience that places the user in high-pressure environments with dynamic spatial constraints. Visual and auditory feedback, along with the ability to switch between multiple drone perspectives, is intended to support situational awareness, mission control, and error recovery in complex terrain.From a human factors perspective, the simulator serves as a flexible testbed for evaluating cognitive and ergonomic variables in safety-critical tasks. It allows the assessment of operator workload, interface usability, attention allocation, and situation awareness under realistic but controlled conditions. Subjective evaluation tools such as the NASA Task Load Index (NASA-TLX) and the Situation Awareness Rating Technique (SART) [2] can be embedded directly within the VR experience. At the same time, objective data from head and hand movement, control inputs, and UAV performance are recorded to gain insight into operator behavior.The simulator integrates high-fidelity UAV dynamics using closed-loop reference model adaptive controllers [3], and can be equipped with tools such as eye tracking, physiological sensors for workload estimation, and visual attention assessment methods like ATTENDO [4]. These additions support deeper analysis of how operators acquire information, prioritize tasks, and shift attention during mission-critical events.Overall, the VR-based UAV simulator addresses a growing need to evaluate and enhance human performance in multi-agent control systems used in emergency operations. It offers a scalable, immersive environment that supports both training and cognitive engineering. Its modular structure allows for future integration of real UAVs, digital mapping capabilities, and adaptive interfaces, making it a valuable platform for advancing human-centered UAV system design.

Control room modernization is critical to extending the life of the 99 operating commercial nuclear power plants (NPP) within the United States. However, due to the lack of evidence demonstrating the efficiency and effectiveness of recent candidate technologies, current NPP control rooms operate without the benefit of various newer technologies now available. As nuclear power plants begin to extend their licenses to continue operating for another 20 years, there is increased interest in modernizing the control room and supplementing the existing control boards with advanced technologies. As part of a series of studies investigating the benefits of advanced control room technologies, the researchers conducted an experimental study to observe the effect of Task-Based Overview Displays (TODs) on operator workload and situation awareness (SA) while completing typical operating scenarios. Researchers employed the Situation Awareness Rating Technique (SART) and the NASA Task Load Index (TLX) as construct measures.

With the continuous development of generative models on face generation, how to distinguish the real and fake face has become an important problem for security. Because of the continuous improvement on the detection accuracy by facial physiological signals, video face forgery detection based on facial physiological signal analysis has received more and more attention, which has become an important research branch in the field of face forgery detection. Currently, most of the research on forgery detection based on physiological signal analysis use biometric features such as blinking patterns, head swings, heart rate signals, and lip movements. However, there hasn’t been much exploration on the usage of gaze features in face forgery detection. Through the analysis of gaze directions in face videos, we have observed differences in the distribution of gaze direction pattern between the real and forged videos. Specifically, real videos tend to have more concentrated gaze distribution within a short period of time, while forged videos have more dispersed gaze distributions. In this paper, we present a novel Deepfake gaze analysis method named DFGaze, to explore spatial-temporal gaze inconsistency for video face forgery detection. Our method uses the gaze analysis model (GAM) to analyze the gaze features of face video frames, and then applies a spatial-temporal feature aggregator to realize authenticity classification based on gaze features. In order to better mine the authenticity clues in the videos, we further use the texture analysis model (TAM) and attribute analysis model (AAM) to improve the representation ability of spatial-temporal feature differences between real and forged faces. Extensive experiments show that our method can achieve state-of-the-art performance with the help of gaze analysis. The source code is available at https://github.com/ziminMIAO/DFGaze.

BACKGROUND: Flight cadets' emotion is a factor of great importance to flight training. So it is of profound significance to address how emotional factors affect flight training performance. The present study aimed to investigate the relationship between emotional intelligence (EI) and simulated flight performance (SFP), and explore the mechanism of emotional state as a mediator in the effect of EI on SFP.METHODS: Ninety undergraduates took part in the study. EI (Wong and Law Emotional Intelligence Scale), neuroticism (Eysenck Personality Questionnaire Revised), anxiety (State Anxiety Inventory), and tension (Profile of Mood States) were collected. Conducted were 9 h of simulated flight training in a simulator of the Type 6 Primary Trainer. The Delphi Experts Grading Method was used to assess students' SFP. Mediation effect of emotional state was explored using regression analysis.RESULTS: EI was significantly correlated with neuroticism (r = -0.31), tension (r = -0.31), and anxiety (r = -0.31), respectively. Multiple mediation effects showed that emotional state mediated the association between EI and SFP. Tension especially mediated the associations between the Self Emotion Appraisals and Regulation of Emotion dimensions of EI and SFP. However, the Use of Emotion dimension of EI had a direct negative effect on SFP without the mediating role of emotional state.DISCUSSION: The findings indicated that EI was significantly correlated with emotional state (neuroticism, tension, and anxiety). EI may directly or indirectly affect SFP and tension played an important mediating role. Implications for the promotion of EI and emotional state to enhance performance in real flight training are discussed.Dai J, Wang H, Yang L, Wen Z. Emotional intelligence and emotional state effects on simulated flight performance. Aerosp Med Hum Perform. 2019; 90(2):101-108.

Assessing pilot trainees’ Situation Awareness (SA) is critical for aviation safety and efficiency. This study aimed to evaluate the effectiveness of three distinct eye-tracking metrics, gaze-based metrics, gaze patterns, and gaze entropy, in measuring the SA levels of pilot trainees. A between-subject experiment compared two trainee groups: one received standard training, and the other received training enhanced with vibrotactile feedback. Participants’ eye movements were recorded using wearable eye-tracking glasses before and after training. The experimental group showed improved flight performance, advanced gaze-based metrics, more organized gaze patterns, and increased gaze entropy. These results demonstrate that eye-tracking metrics can effectively reflect SA changes, with gaze entropy significantly correlating with SA measurements and indicating higher SA levels. The study highlights the feasibility of using eye-tracking to evaluate SA in pilot training. Future research should explore varied task complexities and extended training durations to validate these findings and assess long-term impacts.

This research examined the role of working memory (WM) capacity and long-term working memory (LT-WM) in flight situation awareness (SA). We developed spatial and verbal measures of WM capacity and LT-WM skill and then determined the ability of these measures to predict pilot performance on SA tasks. Although both spatial measures of WM capacity and LT-WM skills were important predictors of SA performance, their importance varied as a function of pilot expertise. Spatial WM capacity was most predictive of SA performance for novices, whereas spatial LTWM skill based on configurations of control flight elements (attitude and power) was most predictive for experts. Furthermore, evidence for an interactive role of WM and LT-WM mechanisms was indicated. Actual or potential applications of this research include cognitive analysis of pilot expertise and aviation training.

Incorporation of a dichotic listening task of selective attention in the pilot selection test battery of the Israeli Air Force was studied using a group of 2000 flight cadets. In this test, subjects are presented with 48 auditory messages. Each message is composed of strings of words and digit names. Different strings are simultaneously presented to the two ears. Subjects are required to detect digit names in the relevant channel and to reconsider channel relevance upon indication. Three types of selective listening errors are recorded: omissions, intrusions, and switching errors. Flight cadets who had completed a two-year training program had significantly lower error scores on all attention measures. In addition, these measures had low correlations with all other tests of the pilot selection battery. Thus, attention capabilities appear to be an independent dimension that enhances the predictive validity of the present test battery.