Human factors flight trial analysis for 2D/3D SVS

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.

Purpose This study aims to evaluate flight cadets’ situational awareness (SA) during crosswind landing scenarios to enhance flight performance and optimize training strategies by developing a facial expression-based assessment method tailored to civil aviation training contexts. Design/methodology/approach Cadets performed crosswind landing simulations on an Intermediate Trainer Aircraft Simulator while facial videos were recorded to extract multimodal features, including Action Units (AUs) and gaze directions. Symmetric Dot Pattern (SDP) analysis quantified variations in curvature, thickness, geometric center position and regional orientation over time. Clustering algorithms were used to identify measurable patterns between situational awareness rating technique -rated SA levels and extracted features, which were then classified using Random Forest, XGBoost, LightGBM and AdaBoost models with hyperparameter tuning and key feature selection. Findings Experimental results show that combining AUs and gaze features with the optimized LightGBM algorithm can effectively support the trainees’ SA ability assessment in flight training. Practical implications Provides an objective, data-driven tool for assessing cadets’ SA in flight simulations, supporting targeted training strategies and improving aviation safety. Originality/value Among the first to integrate facial AUs, gaze analysis and SDP technology with advanced machine learning for SA assessment, offering a novel, non-intrusive approach bridging human factors and intelligent aviation training systems.

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 General Aviation Element of the Aviation Safety Program's Synthetic Vision Systems (SVS) Project is developing technology to eliminate low visibility induced General Aviation (GA) accidents. SVS displays present computer generated 3-dimensional imagery of the surrounding terrain on the Primary Flight Display (PFD) to greatly enhance pilot's situation awareness (SA), reducing or eliminating Controlled Flight into Terrain, as well as Low-Visibility Loss of Control accidents. SVS-conducted research is facilitating development of display concepts that provide the pilot with an unobstructed view of the outside terrain, regardless of weather conditions and time of day. A critical component of SVS displays is the appropriate presentation of terrain to the pilot. An experimental study is being conducted at NASA Langley Research Center (LaRC) to explore and quantify the relationship between the realism of the terrain presentation and resulting enhancements of pilot SA and performance. Composed of complementary simulation and flight test efforts, Terrain Portrayal for Head-Down Displays (TP-HDD) experiments will help researchers evaluate critical terrain portrayal concepts. The experimental effort is to provide data to enable design trades that optimize SVS applications, as well as develop requirements and recommendations to facilitate the certification process. In this part of the experiment a fixed based flight simulator was equipped with various types of Head Down flight displays, ranging from conventional round dials (typical of most GA aircraft) to glass cockpit style PFD's. The variations of the PFD included an assortment of texturing and Digital Elevation Model (DEM) resolution combinations. A test matrix of 10 terrain display configurations (in addition to the baseline displays) were evaluated by 27 pilots of various backgrounds and experience levels. Qualitative (questionnaires) and quantitative (pilot performance and physiological) data were collected during the experimental runs. This paper focuses on the experimental set-up and final physiological results of the TP-HDD simulation experiment. The physiological measures of skin temperature, heart rate, and muscle response, show a decreased engagement (while using the synthetic vision displays as compared to the baseline conventional display) of the sympathetic and somatic nervous system responses which, in turn, indicates a reduced level of mental workload. This decreased level of workload is expected to enable improvement in the pilot's situation and terrain awareness.

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.

Du Pont makes titanium: Nucleonics, Vol. 3. No. 4

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

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.

Traffic Aware Strategic Aircrew Requests (TASAR) is a NASA-developed on-board automation concept intended to identify trajectory improvement opportunities clear of known traffic, weather, and airspace restrictions prior to the aircrew initiating a trajectory-change request to Air Traffic Control (ATC). The software implementation of the TASAR concept is the Traffic Aware Planner (TAP). A flight trial was conducted with commercial airline pilots flying in a Piaggio Avanti flight test aircraft, with the TAP software installed onboard. This paper focuses on the results of the subjective assessments of pilots collected during this flight trial, specifically, pilot workload, situation awareness, and system usability. These data were subjected to statistical analyses, and the results generally indicate the following: there were no statistical differences for any measure as a function of pilot position in the aircraft; pilot cognitive workload was reported as low; and system usability ratings were reported as high. Generally, ratings of comprehensibility, usefulness, and usability of TAP’s human machine interface (HMI) and features were high. These results will be used to further refine and improve the capabilities and features of the TAP HMI in preparation for operational use with NASA partner airlines.

Recent inventions of Augmented Reality (AR) Head-Mounted-Device (HMD) devices such as Microsoft’s HoloLens have allowed certain innovations that up till now were only able to exist in Science Fiction. The ability to project holograms within a space have been used in the Aerospace industry since 2016, when the HoloLens was first released. However, the aviation industry has yet to harness the capability that such a device can allow. The conversion of a traditional 2D Primary Flight Display (PFD)to a Volumetric 3D representation of the PFD was explored. The 3D representation of the PFD was created in Unity 3D, and by means of the Holographic Remoting Tool the graphics were displayed on to the HoloLens. The symbology on the PFD was driven by live flight data from a flight simulator. For thisproject two different 3D PFD models were created one for a fixed-winged based aircraft, and another fora quadcopter. Two different flight simulators were used for the two different PFDs. For the fixed-wingedPFD the Digital Combat Simulator (DCS) World by Eagle Dynamics was used, and for the quadcopterPFD the AirSim plugin by Microsoft was ran using Unreal Engine 4 (UE4). Through testing it was found that both the PFD models assist the pilots to safely keep their aircraft in the air and also perform an emergency landing by only using the 3D PFD. Another conclusion made was that in its current state the3D PFD is ideal for Unmanned Arial Vehicle (UAV) pilots as a holographic Ground Control Station(GCS)

Helicopter landings on unprepared sites can quickly become a challenging task. Especially when environmental factors reduce the available visual cues for the pilot, the risk of disorientation increases. Motivated by avoiding accidents during helicopter approaches, a novel pilot assistance system was developed by a workgroup from the German Aerospace Center (DLR) and HENSOLDT Sensors GmbH. The research system combines 3D conformal tunnel-in-the-sky symbology with dynamic path updates driven by a laser sensor. In early 2017, the system was evaluated in flight using DLR's research rotorcraft Active Control Technology/Flying Helicopter Simulator (ACT/FHS). The workgroup was tasked to participate in flight trials with U.S. and Swiss teams during the NATO sponsored flight trials within the scope of the DVE-Mitigation (DVE-M) program. In this program, international efforts in the development of systems for enhanced situational awareness during DVE are supported. The evaluation of the system during the DVE-M trials included approaches which were obstructed by a truck with a 20m high man lift. Four external test pilots participated in the evaluations. Following the positive results obtained during these trials, two further flights were conducted in local scenery at Braunschweig/Wolfsburg airport, including a construction site with a hangar and a crane. Results of these six flights are presented and discussed in detail.