Pilot performance evaluation of simulated flight approach and landing manoeuvres using quantitative assessment tools

Hebbar, P. Archana; Pashilkar, AA

doi:10.1007/s12046-017-0613-0

Cited by 8 publications

(6 citation statements)

References 9 publications

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“…Participants' inceptor control strategy, together with his/her flying performance, indicates his/her cognitive workload (Hebbar and Pashilkar, 2017). Accordingly, we computed flight performance in terms of RMSE in altitude and airspeed deviations (Figure 11).…”

Section: Flying Performance Analysismentioning

confidence: 99%

Correlation Between Physiological and Performance-Based Metrics to Estimate Pilots' Cognitive Workload

Hebbar

Bhattacharya²,

Prabhakar³

et al. 2021

Front. Psychol.

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This paper discusses the utilization of pilots' physiological indications such as electroencephalographic (EEG) signals, ocular parameters, and pilot performance-based quantitative metrics to estimate cognitive workload. The study aims to derive a non-invasive technique to estimate pilot's cognitive workload and study their correlation with standard physiological parameters. Initially, we conducted a set of user trials using well-established psychometric tests for evaluating the effectiveness of pupil and gaze-based ocular metrics for estimating cognitive workload at different levels of task difficulty and lighting conditions. Later, we conducted user trials with the NALSim flight simulator using a business class Learjet aircraft model. We analyzed participants' ocular parameters, power levels of different EEG frequency bands, and flight parameters for estimating variations in cognitive workload. Results indicate that introduction of secondary task increases pilot's cognitive workload significantly. The beta frequency band of EEG, nearest neighborhood index specifying distribution of gaze fixation, L1 Norm of power spectral density of pupil diameter, and the duty cycle metric indicated variations in cognitive workload.

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Section: Flying Performance Analysismentioning

confidence: 99%

Correlation Between Physiological and Performance-Based Metrics to Estimate Pilots' Cognitive Workload

Hebbar

Bhattacharya²,

Prabhakar³

et al. 2021

Front. Psychol.

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show abstract

“…But none of these studies provide quantitative comparison of pilot's performance in terms of deviations from the desired flight path or with his/ her visual scan behaviour. Pilot's performance and his/ her workload can be quantitatively measured from traditional metrics using details of his/her control activity and deviations from the predefined flight profile (Hebbar & Pashilkar, 2017). Reasons for pilot's sub-optimal performance can also be gathered from the eye gaze data such as dwell time on pre-defined areas of interest, fixation and pupil diameter.…”

Section: Introductionmentioning

confidence: 99%

Using Eye Tracking System for Aircraft Design – A Flight Simulator Study

2022

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The authors of this paper investigated applications of eye tracking in transport aircraft design evaluations. Piloted simulations were conducted for a complete flight profile including take-off, cruise and landing flight scenario using the transport aircraft flight simulator at CSIR-National Aerospace Laboratories. Thirty-one simulation experiments were carried out with three pilots/engineers while recording the ocular parameters and the flight data. Simulations were repeated for high workload conditions like flying with degraded visibility and during stall. Pilot’s visual scan behaviour and workload levels were analysed using ocular parameters; while comparing with the statistical deviations from the desired flight path. Conditions for fatigue were also recreated through long duration simulations and signatures for the same from the ocular parameters were assessed. Results from the study found correlation between the statistical inferences obtained from the ocular parameters with those obtained from the flight path deviations. The authors of this paper investigated an evaluator’s console that assists the designers or evaluators for better understanding of pilot’s attentional resource allocation.

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“…Behavioral measures that target workload are of importance in the understanding of learning [13], and adaptive human-controlled systems [14]. Hebbar and Pashilkar [15] argued that these parameter deviations do not sufficiently reflect changes in workload on their own, as pilots are generally able to perform well under demanding conditions. While performance measures are often associated with workload, people can experience a variety of workload levels while maintaining the same level of performance, for example, due to (in)experience and task awareness [16], [17], but also due to task characteristics such as task duration and the required level of information processing [18].…”

Section: Introductionmentioning

confidence: 99%

“…While performance measures are often associated with workload, people can experience a variety of workload levels while maintaining the same level of performance, for example, due to (in)experience and task awareness [16], [17], but also due to task characteristics such as task duration and the required level of information processing [18]. Therefore, to reliably assess a pilot's workload, Hebbar and Pashilkar [15] suggested to quantify pilot control over the inceptors in the (simulator) cockpit, such as the stick. Stick control serves as a direct measure of the human operation and interaction with the (virtual) aircraft and hence provides valuable information in addition to flight performance measures such as deviations from given parameters or flight paths.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Comparing Presence, Workload, and Performance in Desktop and Virtual Reality Flight Simulations

Weelden

Wiltshire

Alimardani

et al. 2022

Proceedings of the Human Factors and Ergonomics Society Annual

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Virtual reality (VR) offers a training environment that promotes increased learning and performance. However, to what extent VR flight simulations offer increased performance compared to less-immersive simulators is not clear, and neither are their underlying cognitive aspects. In a within-subject experiment, we compared fight performance and subjective measures of workload, presence, and engagement in two flight training environments (Desktop and VR) on two flight tasks of equal difficulty (changing speed and performing turns). No differences were observed in the flight performance between these conditions. However, participants reported higher presence and engagement in the VR training environment. Additionally, we found a correlation between subjective workload and flight performance in the Desktop condition, but not in VR. We conclude that VR is promising for basic flight training tasks and encourage future work to explore this further by investigating neurophysiological indices of workload and engagement and establishing relationships between presence, workload, and flight performance.

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Pilot performance evaluation of simulated flight approach and landing manoeuvres using quantitative assessment tools

Cited by 8 publications

References 9 publications

Correlation Between Physiological and Performance-Based Metrics to Estimate Pilots' Cognitive Workload

Correlation Between Physiological and Performance-Based Metrics to Estimate Pilots' Cognitive Workload

Using Eye Tracking System for Aircraft Design – A Flight Simulator Study

Comparing Presence, Workload, and Performance in Desktop and Virtual Reality Flight Simulations

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