Pilot Situation Awareness Research Articles

Enhancing pilot vigilance assessment: The role of flight data and continuous performance test in detecting random attention loss in short IFR flights

Situational awareness (SA) and fatigue management are crucial aspects of aviation safety, particularly during demanding flight phases. This study introduces an innovative approach employing flight data, machine learning, and Continuous Performance Test (CPT) metrics to predict pilot performance and SA during instrument approaches under Instrument Meteorological Conditions (IMC). Data were collected from over 10 pilots across more than 40 flights in a high-fidelity Cessna 172 analog flight simulator.Significant correlations were observed between dynamic cognitive performance parameters and the exceedance shape factor, a novel measure of pilot sustained attention introduced in this research. Key variables identified through correlation analysis included variability, interstimulus change, and reaction time standard deviation.Importantly, commission scores and reaction time standard deviation emerged as key predictors in the machine learning model, specifically the Optimizable Gaussian Process Regression (GPR) model with a radial basis function kernel. The model achieved a validation R-squared of 0.90 and a test R-squared of 0.70. These systems could incorporate additional data sources, such as eye-tracking and scan pattern analysis, for a better assessment of pilot SA and fatigue levels. While post-flight measurements are inherently reactive, they are effective for monitoring the degradation of pilot CPT scores after each leg of high-frequency, short-duration flights.Notable limitations include the need to understand individual cognitive differences among pilots, such as age, experience, and cognitive style. The predictive model also requires validation in actual flight conditions to determine its ecological validity. Future research should aim to address these limitations, generalize the findings, and integrate CPT data with other sensor inputs to provide a more comprehensive understanding of pilot performance.

BASIC PRINCIPLES OF BUILDING INTELLIGENT SYSTEMS FLIGHT CONTROL

The issues of creating intelligent control systems in a dynamically changing flight environment are considered and the principle of constructing an onboard intelligent flight control system is proposed. The implementation of the proposed system is based on the pilot's situational awareness of the flight progress in real time, which allows avoiding errors and maintaining enhanced synergy between human and avionics systems. Constant adaptation of the cockpit, as well as onboard. automation successfully maintains the pilot's workload within an optimal range, mitigating the occurrence of dangerous levels of fatigue. Methods for assessing and predicting the threat of an aviation accident based on direct control of the variation in the values of characteristics that affect flight safety, using methods and tools of artificial intelligence, are proposed. Keywords: flight safety, aircraft, intelligent aviation system, accident threat, prevention, control system, artificial intelligence, aircraft control systems

Development of Hud Symbology for Enhanced Vision System

Head-up display is one of the important sub-systems of aircraft avionics suite for enhancing pilot situational awareness for smooth and safe gate-to-gate operations especially during take-off, approach and landing phases of flight. The Head-up display consist of generic and advanced sets of symbologies mainly categorized as i) conformal: such as local horizon, airport/runway, highway-in-the-sky, pitch ladder, etc and ii) non-conformal: airspeed, altitude, heading, roll, horizontal situation indicator etc. These symbologies can be combined or overlaid with more advanced systems such as Enhanced vision system/synthetic vision system to increase pilot situational awareness in case of poor weather conditions/ degraded visual environment. This paper presents development of generic and enhanced vision system specific Head-up display symbologies based on Gulfstream G450 Head-up display standard and its integration with in-house developed Enhanced synthetic vision system flight simulator.

Designing augmented reality for future commercial aviation: a user-requirement analysis with commercial aviation pilots

Augmented reality (AR) capable head-mounted displays (HMDs) have been proposed as technological enablers of several complex future flight concepts, which will bring accompanying pilot situation awareness (SA) and operational safety enhancements. However, relevant aviation design guidance concerning the implementation of modern HMD technologies and AR symbology is sparse. Consequently, the current study describes an SA grounded user-requirements analysis of operational applications for HMD technologies and AR symbology, with the intention of providing inputs for future designs of commercial aviation systems. In addition, insights from the study are relevant for AR design more generally. Endsley’s three-level SA model (1988) was applied as a framework to focus group discussions with eleven aviation subject matter experts. Thematic analysis highlighted multiple operational scenarios where HMD technology and AR may enhance SA, along with the requirements of the technologies to provide these relevant advantages. In future, more detailed user-centred design recommendations should be sought for the specific applications identified within the current study.

The Influence of Emotion Induced by Accidents and Incidents on Pilots' Situation Awareness.

(1) Background: This study examines the differences in emotions induced by accidents and incidents as emotional stimuli and the effects on pilot situation awareness (SA) after induction. (2) Method: Forty-five jet pilots were randomly divided into three groups after which their emotions were induced using the pictures of accident, incident, and neutral stimulus, respectively. (3) Results: The conditions of accidents and incidents both induced changes in the pilots' happiness and sadness and the changes in the emotion were regulated by the emotional intelligence of pilots in the high SA group. The emotion induction, which caused a direct change in pilot's happiness and fear, resulted in conditions that indirectly affected level 1 of SA in pilots. (4) Conclusions: The research elucidates the difference between accident and incident in inducing pilot emotions, and reminds us that SA level exerts the regulating effects on the same emotional induction conditions.

Influencing factors of novice pilot SA based on DEMATEL-AISM method: From pilots’ view

Pilot situation awareness (SA) regulates flight safety, and inexperience may impair novice pilot reliability in SA. This study aims to determine the key influencing factors of novice pilot SA and to analyze the interrelationship and interaction mechanism of the factors. We investigated 55 novice pilots trained at aviation schools and identified the influencing factor index system by the Delphi survey. The method of Decision Making Trial and Evaluation (DEMATEL) combined with Adversarial Interpretive Structure Modeling (AISM) was adopted. The results show that: (1) The influencing factor index system includes 18 factors, divided into four categories: individual factors, team factors, task and human-machine system factors, and cockpit environment factors. (2) Team communication, team cooperation, basic cognitive ability, interface design, occupational age and experience, and authority gradient are the six crucial influencing factors. The former three have the greatest association with other factors, while the latter three are most likely to affect other factors. (3) Team communication, basic cognitive ability, and interface design are root-cause factors, of which team communication is the most fundamental. (4) The results of DEMATEL and AISM are consistent, both disclosing team communication as the fundamental factor with the highest priority, and cockpit environmental factors as the direct influencing factors but most susceptible to other factors. The present study can be viewed as a conducive attempt to extract vital influencing factors of novice pilot SA, and to provide ergonomic insights for determining the priorities to improve novice pilot SA in training and aircraft design for flight safety.

The influence of augmented reality interaction design on Pilot's perceived workload and situation awareness

This work explored the potential for Augmented Reality (AR) rendering information superimposed over the flight deck to increase a pilot's situation awareness (SA). This emerging technology introduced novel human-computer interaction paradigms that would have impact on pilot's cognitive demands. The objective of this research was to evaluate both the pilot's perceived workload and SA while interacting with an AR device using different interactive modes. Participants performed traditional landing checklists as a baseline to compare with the AR gesture-command and voice-command checklists. The research results showed that gesture-commands created additional cognitive and physical demands. Conversely, voice-command checklists could constitute a significant improvement in terms of reducing participants' perceived workload and maximising SA performance. The findings provided evidence that the interactive modes of AR user interface design could influence participant's cognitive information processing and perceived workload in flight operations. However, there were some limitations with AR applications that included latency on response time, narrow field of view, accuracy of voice recognition, calibration within dynamic environment and inexplicable movements of the head position that required further investigation. An AR device can be a great tool for training at the initial stage to increase cost-efficiency in flight operations. Furthermore, the implementation of an AR design may provide part of the potential solution for single pilot operations in the future.

Evaluation of Auto Pilot Situational Awareness System Using Gunshot Detection Algorithm in a Localized Environment: Case Study Federal Polytechnic Offa, Mini Campus

Gunshot detection technologies are more applicable in many industries for the security enhancement of public places like the Federal Republic Territory FCT Abuja in Nigeria. Many factors affect the accuracy of the gun detection algorithm. This paper describes an audio-based video surveillance system in an auto pilot situational awareness to detect gunshots in Federal Polytechnic Offa. The Time Difference of Arrival (TDOA) of Shock Wave and Muzzle Blast is integrated to estimate the shooter location in the study are. The proposed design and algorithm was validated and shooter origin was resolute that was very close to theoretical values. The video camera is steering regarding the initial position to localize the acoustic source's position. Implementing an auto pilot situational awareness system is an experimental procedure with a gunshot detection algorithm in a localized environment. In the direction of the weapon, the distance between firearms, types of ammunition, types of study environment, and diffraction of audio, the standard feature for gunshot recognition are Mel frequency cepstral coefficients in terms of uniform gamma-tone filters linearly spaced over the whole frequency range from 0KHZ to 16KHZ. Experiments show that our system can detect gunshots with a precision of 93% at a false rejection rate of 5% when the SNR is 10db while proving the estimate of the source direction of the gunshot with an accuracy of one degree. The outcomes reveal that the data generated by the system can be leveraged by the firefighting department to quickly locate the whereabouts of the indoor fires, and the VR gamification scenarios can expedite the development of situational awareness for the trainees. The research recommends a real-time system implementation for protecting the Federal Polytechnic Offa against any form of treats.

Machine Learning to Improve Situational Awareness in Beyond Visual Range Air Combat

This article presents an artificial intelligence model using artificial neural networks that provide parameters to improve the situational awareness of a Beyond Visual Range (BVR) air combat pilot. In this combat modality, it is necessary to make decisions based on information from sensors, mainly radars. Furthermore, since information regarding enemy aircraft systems is sometimes unknown, pilots' decisions are usually based on beliefs regarding the opponent. The presented model proposes to deal with such characteristics, generating behaviors for entities represented in a constructive simulation environment, i.e., simulated people operating simulated systems. We created BVR air combat simulations between two aircraft, with only one missile each, through Latin Hypercube Sampling (LHS) to choose input variables to cover almost homogeneously all their ranges. The aircraft have similar behaviors, and their parameters may change only at the beginning of the simulation. The simulation environment generated ten thousand air combat scenarios, varying thirty-six input parameters, for the analysis proposed in the case study. From this data, we could create supervised machine learning models that substantially improve the BVR air combat pilot's situational awareness regarding offensive situations, in which the reference aircraft employs a missile against a target, or defensive positions, in contrast to when the same reference aircraft tries to avoid a possible enemy's missile launched in its direction. The offensive and defensive models were consistent with the accuracy of 0.930 and 0.924 and the F1-score of 0.717 and 0.678, respectively. Thus, the contribution of this work is to use machine learning algorithms to generate responses concerning the tactical state to improve the pilot's situational awareness and, therefore, the in-flight decision-making process.

KAJIAN LITERATUR KESADARAN SITUASIONAL PILOT DI BIDANG PENERBANGAN

Situational awareness is an important aspect that a pilot must have as an operator in the aviation sector. This aspect plays an important role in maintaining safety in flight operations. Situational awareness is also an important material in the education and training of prospective pilots. The situational awareness study among pilots is an important study to do. The purpose of writing this article is to conduct a literature review of pilot situational awareness in the field of aviation. The study was conducted by searching the literature for research publications within the last 25 years. The review is carried out by compiling research summaries sequentially according to the year of publication. Research topic grouping is done to get the amount of research according to the topic and topic area. The analysis is carried out to get an overview of future research trends. The results of the study show that the number of research tends to increase after 2015. While the research topics that are mostly studied are the implementation and analysis of pilot situational awareness.

Multi-agent modelling and situational awareness analysis of human-computer interaction in the aircraft cockpit: A case study

The loss of situational awareness by pilots is one of the harshest risk factors leading to catastrophic accidents. In this paper a situational awareness analysis model based on multiple agents is presented to simulate the human-computer interaction process in the aircraft cockpit. From the perspective of human-in-loop, the integrated model consists of modularized pilot agent model, technical system agent model and environment agent model. Following the structured levels of situational awareness, the pilot's cognitive behaviors are modelled based on Adaptive Control of Thought-Rational (ACT-R) theory and Bayesian network, with the triggering inputs from the visual and auditory sensory channels. Considering the effects of overlapping information from different channels, the formation and evolution mechanism of the pilot's situational awareness is analyzed in a probabilistic inference manner. The tests of input-output characteristics prove that the model can well reflect the distribution and resist the uncertain fluctuation of different cognitive elements. The safety issues based on two simplified real risk scenarios, under the background of the incidents/accidents related with Boeing 737-8 (MAX), were analyzed. The mechanism of accident evolution along with the possible preventive measures were discussed. It is concluded that an early control priority transmission from the technical system to the pilots and the display of direct prompt messages could make a difference in avoiding the serious risk.

An approach to situation awareness (SA) assessment in flight simulation: SA dynamic circulation (SADC) model

AbstractAccurate prediction and evaluation of pilot's situation awareness (SA) are of great importance for ensuring flight safety. In the present study, an SA dynamic circulation (SADC) model is developed for describing the dynamic generation and update processes of pilot's SA in‐flight environments. In the SADC model, five cognitive statuses of SA, which constitute the dynamic circulation in a closed‐loop network, are put forward on a framework of adaptive control of thought rational‐queuing network. By introducing the progressive triggers of the low and high SA, pilot's SA covering three levels is computed using conditional probability. In addition, flight simulations based on four typical flight scenarios were performed to verify the usability of the SADC model, and multiple methods including the subjective evaluation, situation present assessment method (SPAM), and physiological measurement were adopted for SA measurement. According to the results, the rationality of the SADC model is validated due to the significant correlations between SA theoretical prediction value and SPAM response time as well as 10D‐SART score. Besides, in our study, the SPAM response time and 10D‐SART score show an acceptable sensitivity to SA measurement, however, physiological indicators of respiratory rate and standard deviation of normal to normal RR intervals are proved more sensitive to workload rather than SA. The SADC model is expected to be applied in the quantitative characterization of pilot's SA as a new auxiliary analysis tool during cockpit display interface design and flight training strategy optimization.

AIRLINE PILOT SITUATION AWARENESS: PRESENTING A CONCEPTUAL MODEL FOR META-COGNITION, REFLECTION AND EDUCATION

The dissertation research summarized here, utilized the Grounded Theory Method to develop a conceptual model of pilot situation awareness from 223 Aviation Safety Reporting System (ASRS) narratives. The application of Latent Semantic Analysis aided the theoretical sampling of ASRS reports. A multistage model was developed involving attention, perception, interpretation, decision making, and action in support of goal-driven behavior. Narrative report coding identified several categories of situation awareness elements that pilots direct their attention to in building and maintaining situation awareness. Internal to the aircraft, flight crews directed their attention to the aircraft’s flight state and automation state. They also directed their attention to the condition of the aircraft, the functioning of the crew, and the status of the cabin. External to the aircraft, flight crews directed their attention to airport conditions, air traffic control, terrain, traffic, and weather. Pilots were also aware of the passage of time. Twelve characteristics of situation awareness were identified from narrative report coding which were subsequently compared with existing theoretical perspectives of situation awareness.

Autonomous Guidance and Flight Control on a Partial-Authority Black Hawk Helicopter

An autonomous guidance and flight control system was integrated and flight tested on a Black Hawk helicopter as part of an effort to provide all weather capability for U.S. Army fleet rotorcraft. The guidance and flight-control system components were previously flight tested on a full-authority helicopter, and were adapted to fly on the partial-authority test helicopter of this paper. The main autonomy guidance components consisted of the Risk Minimizing Obstacle Field Navigation algorithm, Safe Landing Area Determination algorithm, Mission Manager, and Integrated Cueing Environment. These components provided reactive obstacle avoidance guidance, landing site selection, pilot/autonomy interaction, and pilot situational awareness for degraded visual environments. In addition to the autonomy components, the Autonomous Partial-Authority Flight Control System provided a fully stabilized path-following capability to the guidance components. This paper describes how these components were adapted to a partial-authority helicopter that is typical of the current U.S. Army fleet. To test the system, a laser detection and ranging unit was used as a surrogate ranging device in lieu of an all-weather sensor system that was concurrently under development. Flight test results are presented from the fully integrated system navigating through terrain, selecting landing sites, and autonomously landing, while simultaneously keeping the pilot situationally aware of the autonomy’s intent.

Identifying Cognitive Mechanism Underlying Situation Awareness of Pilots' Unsafe Behaviors Using Quantitative Modeling.

Situation awareness (SA) of pilots’ unsafe behavior can ensure safety onboard. Thus, the cognitive mechanism that controls the SA leading to unsafe behavior must be articulated. This study employs the SA model and theory of planned behavior (TPB) to articulate a quantitative model of ship safe piloting. Firstly, the hierarchical classification framework of unsafe behaviors was constructed as an analytical foundation for rational and unconscious behaviors in sight of cognitive processes, and then the measurement elements of the cognitive mechanisms for behaviors were identified. Subsequently, based on the structural model, a hypothetical model of the cognitive path for unsafe behaviors was proposed by using the extended TPB, where there are four independent variables (i.e., attitude (ATD), subjective norm (SN), and perceived behavioral control (PBC)), one mediating variables (i.e., SA) and two dependent variables (i.e., behavioral intention (BI) and unsafe behaviors (BE)). Finally, this hypothetical model was analyzed with the data resources from extended TPB questionnaire of 295 pilots. Analysis results show that relationships of causation and mediation in the cognitive mechanism are in line with the behavior pattern and SA have a pronounced mediating effect and a strong relevance to the causal chain of extended TPB framework. This study integrated the SA three-level model to understand the motivation–cognition–action–feedback (MCAF) mechanism of pilots’ unsafe behaviors under cognitive mode of information processing through structural model. It would make a valuable contribution to the assessment and intervention of safety behaviors, and provide a basic framework for monitoring the situation awareness of pilot by man-machine interactive measurement technology in the future.

Advanced technologies of the pilotage service in the sea and river ports of the Arctic zone of the RF

In a significant number of waters with difficult navigation conditions, especially in the waters of the sea and river ports of the Arctic, despite the presence of a wide range of modern information and navigation aids, pilotage is actively used. In some cases, the pilot's situational awareness in difficult meteorological conditions is insufficient, which necessitates the introduction of more advanced information sensors and communication tools. To solve this problem, it is necessary to develop proposals on the principles of building technical means for increasing situational awareness during pilotage in sea and river ports of the Arctic zone of Russia. This article proposes the concept of constructing a system for providing a pilot with additional highly detailed information based on the technology of broadband data transmission of a highly informative port radar station directly to the pilot's terminal with visualization of the real picture of the navigation situation. The application of the proposed principles of building information support systems for pilotage services in ports will improve the efficiency and safety of navigating ships in the port water area and on approaches to the port, increase the rate of information exchange between the control point and the ship's crew (pilot), and create prerequisites for automating ship management processes. The use of a new generation of highly informative radars and mobile terminals associated with them via broadband communication channels ensures the creation of a local navigation system for navigation. That ensures pilotage in the Arctic zone of ships of any type, including those without high-quality ship radars, and provides automation of the assessment of threatening situations and solutions for them prevention even with unstable operation of satellite navigation systems. In essence, this technology is the first step towards increasing the automation of navigation in ports and ship passages.

Developing an Improved ACT-R Model for Pilot Situation Awareness Measurement

According to a previously built situation-awareness (SA) model based on attention allocation, with the ACT-R (Adaptive Control of Thought, Rational) theory for analyzing pilot cognitive processes for situation elements, an SA mathematical model was improved to predict pilot SA during exposure to different display interfaces and missions. An indicator-display monitoring task was performed under different experimental conditions for SA model verification, while the SA global assessment technique (SAGAT), performance measures, 10-dimensional SA rating technique (10-D SART), and eye movement measures were adopted to comprehensively assess the operator’s SA. The experimental results revealed that theoretical prediction values calculated using the improved SA model were strongly correlated with the operation performance, and thus confirming the model validation. The SAGAT was shown to be a more effective method than SART in this research, and the overall SAGAT accuracy rate, as well as the accuracy response time, are effective indices for SA measurement. Eye-movement indices, such as the fixation/saccade ratio, which corresponds to the mode of information perception and extraction, was examined to be sensitive to operator’s SA changes. The Advances of the improved SA model have been achieved in predicting and indicating SA by using human behaviors, including operation performance, SAGAT response behaviors, and visual behaviors. Thereby, it provides a new auxiliary tool for quantitative characterization of pilot’s SA during cockpit interface design optimization and ergonomic evaluation.

Remote Pilot Situational Awareness with Augmented Reality Glasses: An Observational Field Study

With the use of small unmanned aerial systems (sUAS) proliferating throughout industry and public safety, it is imperative to ensure safety of flight. The Federal Aviation Administration (FAA) published regulations for commercial use of sUAS in 2016 and included the requirement to maintain visual line-of-sight with the aircraft at all times. However, due to the nature of the sUAS ground control stations (GCS), remote pilots time-share between observing the aircraft and interacting with the display on the GCS. Time-sharing between the aircraft and GCS can be seen as similar to the cross-check a pilot uses when flying a manned aircraft. While manned aircraft designers have invested in the ergonomics and understanding of the cognitive process to optimize situational awareness, it has not been a design requirement for sUAS. The result is that the unmanned operator must change head orientation, eye focus, and remove the aircraft from peripheral vision during the cross-check between the GCS and aircraft. This, coupled with the limited field of view of the sUAS GCS displayed camera, leads to loss of situational awareness through task saturation, and misprioritization. Mixed reality, virtual reality, and augmented reality visual devices are being adopted in the gaming and technical world. The application of these devices to the sUAS GCS could mitigate some of the degradation of situational awareness. Specifically, the incorporation of augmented reality devices where a synthetic display is overlaid on the real-world, allows the remote pilot to observe the aircraft, manipulate the camera, and interact with the GCS without changing head position. This participant observational study evaluated the difference between the remote pilot cross-check while flying with a typical GCS display and when flying with an augmented reality headset in a field setting. The results indicate a significant difference between the pilot’s crosscheck when using augmented reality glasses allowing the pilot to maintain the aircraft in their field of view 56.7% of the time compared to 20.5% when not using the glasses.

Quantitative assessment and visualization of flight risk induced by coupled multi-factor under icing conditions

Aircraft icing has been proven to be one of the most serious threats to flight safety. During the analysis of flight risk under icing conditions, quantitative assessment and visualization of flight risk are quite essential as they provide safe manipulation strategies in intricate conditions. However, they are rarely studied. Since the icing flight accidents are the result of the coupling of multiple unfavorable factors, in present study, we have proposed a method to quantitatively assess flight risk induced by multi-factor coupling under icing conditions by Monte-Carlo simulation and multivariate extreme value theory. The results demonstrate that the flight risk probability increases with the rise of unfavorable factors. Besides, a flight risk visualization method named flight safety window has been presented to build the flight risk distribution cloud maps in different complex conditions. The cloud maps show that the icing would give rise to atrophy of the safety scope, and the consequence would be even more severe when coupled with other more unfavorable factors. The proposed methods in this study would be useful in flight risk analysis under icing conditions and can enhance the pilot's situational awareness in selecting correct strategies within the safety zone to avoid unsafe manipulation.

Operational concept and validation of a new airport low-level wind information system

AbstractPilots are sometimes not provided with sufficient information to avoid go-arounds or other operational disruptions that result from low-level wind disturbances. We identified issues with existing windshear alerting systems and developed three types of airport low-level wind information systems to enhance pilot situational awareness of wind conditions by providing landing aircraft with quantitative and visualised wind information for ultimately mitigating air service disruptions due to low-level wind disturbances. The three systems, Airport Low-level Wind Information (ALWIN) and Low-level Turbulence Advisory System (LOTAS), both of which use Doppler radar/lidar, and Sodar-based Low-level Wind Information (SOLWIN), which uses Doppler SOnic Detection And Ranging (SODAR), have different costs and capabilities that allow the most cost-effective system to be selected for an airport according to its scale and local weather characteristics. This paper presents the operational concepts of our newly developed airport low-level wind information systems and describes their validation.