Pilots' mental workload variation when taking a risk in a flight scenario: a study based on flight simulator experiments

Avoiding automation surprise: Identifying requirements to support pilot intervention in automated Uncrewed Aerial Vehicle (UAV) flight

The breadth and depth of Uncrewed Aerial Vehicle (UAV) operations are expanding at a considerable rate. With expansion comes challenges for the design of automation to support decision making. This research takes the perceptual cycle model (PCM) and the derived trust version of the Schema World Action Research Method (T-SWARM), to identify the issues and challenges of pilot intervention in UAVs operating during highly automated states. Nine UAV pilots with current experience operating medium to large UAVs were interviewed, using T-SWARM, about incidents in which they initiated an intervention in system operation (i.e. to avoid weather or collision) and an event where the system initiated the intervention (i.e. due to system failure). The coded responses highlighted the challenges with what information is displayed, how it is displayed and how it influences decision-making in the UAV context. In addition, the responses also identified aspects that influence trust in the system, including personal disposition, affect interventions with the automation. Against each of the key factors identified recommendations are made to increase safety and operational efficiency of UAV operations. This research adds to the growing body of literature that supports the application of T-SWARM for eliciting knowledge in the aviation domain and specifically within the UAV domain.

Attention demands modulate brain electrical microstates and mental fatigue induced by simulated flight tasks

Objective.Prolonged engagement in tasks with varying attention demands is thought to elicit distinct forms of mental fatigue, potentially indicating variations in neural activity. This study aimed to investigate the association between mental fatigue and changes in electroencephalogram microstate dynamics during tasks with varying attention demands.Approach.In the present study, we employed a 2 × 2 repeated measures ANOVA to analyze the temporal parameters of four distinct microstates (A, B, C, and D) across different levels of attention demands (high vs. low) and mental fatigue (high vs. low) within a controlled flight simulation task involving 17 college students.Main results.Significant variations in mean durations were observed, with microstates A and B exhibiting shorter durations under high fatigue during low attention demands, while their durations increased under high attention demands. Microstate C showed increased occurrences with high fatigue under low attention demands and decreased occurrences under high attention demands. The duration and occurrence of the microstates exhibited different trends throughout the course of mental fatigue, potentially reflecting distinct fatigue-related processes.Significance.These findings establish a link between different types of mental fatigue and microstate dynamics, contributing to a comprehensive understanding of the neural processing mechanisms underlying mental fatigue.

How flight experience impacts pilots' decision-making and visual scanning pattern in low-visibility approaches: preliminary evidence from eye tracking

The visual approach is the most accident-prone phase of a flight, especially in low-visibility conditions. This preliminary study aimed to examine the effects of flight experience on pilots' decision-making and visual scanning pattern in low-visibility approaches. Twenty pilots were separated into two groups based on their flight experience and completed the high- and low-visibility approaches in balanced order using a high-fidelity flight simulator. Pilots' mental workload and visual scanning patterns were recorded via an eye tracker. The results showed that, compared to less flight-experienced pilots (20%, 3/15), experienced pilots (80%, 4/5) were more likely to make go-around decisions in the low-visibility approaches. Furthermore, they exhibited a more flexible and adaptable visual scanning pattern by quickly shifting their attention, as evidenced by decreased fixations and increased saccades. These findings suggest that the integration of visual scanning strategy and training solution with a marginally meteorological approach may enhance decision-making safety for novice pilots.

Development and validation of an assessment index for quantifying cognitive task load in pilots under simulated flight conditions using heart rate variability and principal component analysis

To investigate whether high cognitive task load (CTL) for aircraft pilots can be identified by analysing heart-rate variability, electrocardiograms were recorded while cadet pilots (n = 68) performed the plane tracking, anti-gravity pedalling, and reaction tasks during simulated flight missions. Data for standard electrocardiogram parameters were extracted from the R-R-interval series. In the research phase, low frequency power (LF), high frequency power (HF), normalised HF, and LF/HF differed significantly between high and low CTL conditions (p < .05 for all). A principal component analysis identified three components contributing 90.62% of cumulative heart-rate variance. These principal components were incorporated into a composite index. Validation in a separate group of cadet pilots (n = 139) under similar conditions showed that the index value significantly increased with increasing CTL (p < .05). The heart-rate variability index can be used to objectively identify high CTL flight conditions.Practitioner summary: We used principal component analysis of electrocardiogram data to construct a composite index for identifying high cognitive task load in pilots during simulated flight. We validated the index in a separate group of pilots under similar conditions. The index can be used to improve cadet training and flight safety.Abbreviations: ANOVA: a one-way analysis of variance; AP: anti-gravity pedaling task; CTL: cognitive task load; ECG: electrocardiograms; HR: heart rate; HRV: heart-rate variability; HRVI: heart-rate variability index; PT: plane-tracking task; RMSSD: root-mean square of differences between consecutive R-R intervals; RT: reaction task; SDNN: standard deviation of R-R intervals; HF: high frequency power; HFnu: normalized HF; LF: low frequency power; LFnu: normalized LF; PCA: principal component analysis.

Stress and Workload Assessment in Aviation-A Narrative Review

In aviation, any detail can have massive consequences. Among the potential sources of failure, human error is still the most troublesome to handle. Therefore, research concerning the management of mental workload, attention, and stress is of special interest in aviation. Recognizing conditions in which a pilot is over-challenged or cannot act lucidly could avoid serious outcomes. Furthermore, knowing in depth a pilot's neurophysiological and cognitive-behavioral responses could allow for the optimization of equipment and procedures to minimize risk and increase safety. In addition, it could translate into a general enhancement of both the physical and mental well-being of pilots, producing a healthier and more ergonomic work environment. This review brings together literature on the study of stress and workload in the specific case of pilots of both civil and military aircraft. The most common approaches for studying these phenomena in the avionic context are explored in this review, with a focus on objective methodologies (e.g., the collection and analysis of neurophysiological signals). This review aims to identify the pros, cons, and applicability of the various approaches, to enable the design of an optimal protocol for a comprehensive study of these issues.

The risk-taking behavioural intentions of pilots in adverse weather conditions: an application of the theory of planned behaviour

This paper examined pilots' risk-taking behavioural intentions based on the theory of planned behaviour, as well as the impact of experience on behavioural intentions in adverse weather conditions. Two hundred and seventy-three airline pilots and flying cadets were divided into two groups and asked to complete a questionnaire based on two decision-making scenarios. This questionnaire measured pilots' intentions to take risks, along with the attitude towards the behaviour, subjective norms, perceived behavioural control (PBC), risk perception, and self-identity. The results showed that attitude, subjective norm, PBC, and risk perception explained 52% of the variance in behavioural intentions. Additionally, pilots' risk-taking decisions can be influenced by experience. Inexperienced pilots had a relatively stronger intention to take risks and a more favourable attitude towards risky behaviour. Moreover, pilots were more likely to rely on their own direct experience in the decision-making process. Practitioner summary: This study examined the pilots' risk-taking intentions under adverse weather conditions using a questionnaire based on the TPB theory. Results demonstrated that the TPB model can be applied to the risk-taking scenario and that experience can influence pilots' decisions. These findings have implications for improving flight safety and lowering accident rates.