Kellie D. Kennedy

Quantifying pilot contribution to flight safety for normal and non-normal airline operations

Accident statistics cite the flight crew as a causal factor in over 60% of accidents involving transport category airplanes. Yet, a well-trained and well-qualified pilot is acknowledged as the critical center point of aircraft systems safety and an integral safety component of the entire commercial aviation system. No data currently exists that quantifies the contribution of the flight crew in this role. Neither does data exist for how often the flight crew handles non-normal procedures or system failures on a daily basis in the National Airspace System. A pilot-in-the-loop high fidelity motion simulation study was conducted by the NASA Langley Research Center in partnership with the Federal Aviation Administration (FAA) to evaluate the pilots contribution to flight safety during normal flight and in response to aircraft system failures. Eighteen crews flew various normal and non-normal procedures over a two-day period and their actions were recorded in response to failures. To quantify the humans contribution, crew complement was used as the experiment independent variable in a between-subjects design. Pilot actions and performance when one of the flight crew was impaired were also recorded for comparison against the nominal two-crew operations. This paper details a portion of the results of this study.

Automation and Inattentional Blindness in a Simulated Flight Task

The study reported herein is a subset of a larger investigation on the role of automation in the context of single pilot aviation operations. This portion of the study focused on the relationship between automation and inattentional blindness (IB) occurrences for a runway incursion. The runway incursion critical stimulus was directly relevant to primary task performance. Participants performed the final five minutes of a landing scenario in one of three automation conditions (autopilot, autothrottle, and manual). Sixty non-pilot participants completed this study and 70% (42 of 60) failed to detect the runway incursion critical stimulus. Participants in the partial automation condition were significantly more likely to detect the runway incursion when compared to those in the full automation condition. The odds of participant detection in the full automation condition did not significantly vary from the manual condition. Participants that detected the runway incursion did not have significantly higher scores on any component of the NASA-TLX compared to those who failed to detect. The relationship demonstrated between automation condition and IB occurrence indicates the role of automation in operational attention detriment.

Quantifying pilot contribution to flight safety during drive shaft failure

Accident statistics cite the flight crew as a causal factor in over 60% of large transport aircraft fatal accidents. Yet, a well-trained and well-qualified pilot is acknowledged as the critical center point of aircraft systems safety and an integral safety component of the entire commercial aviation system. The latter statement, while generally accepted, cannot be verified because little or no quantitative data exists on how and how many accidents/incidents are averted by crew actions. A joint NASA/FAA high-fidelity motion-base simulation experiment specifically addressed this void by collecting data to quantify the human (pilot) contribution to safety-of-flight and the methods they use in todays National Airspace System. A human-in-the-loop test was conducted using the FAAs Oklahoma City Flight Simulation Branch Level D-certified B-737-800 simulator to evaluate the pilots contribution to safety-of-flight during routine air carrier flight operations and in response to aircraft system failures. These data are fundamental to and critical for the design and development of future increasingly autonomous systems that can better support the human in the cockpit. Eighteen U.S. airline crews flew various normal and non-normal procedures over a two-day period and their actions were recorded in response to failures. To quantify the humans contribution to safety of flight, crew complement was used as the experiment independent variable in a between-subjects design. Pilot actions and performance during single pilot and reduced crew operations were measured for comparison against the normal two-crew complement during normal and non-normal situations. This paper details the crews actions, including decision-making, and responses while dealing with a drive shaft failure — one of 6 non-normal events that were simulated in this experiment.

Quantifying Pilot Contribution to Flight Safety During Hydraulic Systems Failure

Accident statistics cite the flight crew as a causal factor in over 60% of large transport aircraft fatal accidents. Yet, a well-trained and well-qualified pilot is acknowledged as the critical center point of aircraft systems safety and an integral safety component of the entire commercial aviation system. The latter statement, while generally accepted, cannot be verified because little or no quantitative data exists on how and how many accidents/incidents are averted by crew actions. A joint NASA/FAA high-fidelity motion-base human-in-the-loop test was conducted using a Level D certified Boeing 737-800 simulator to evaluate the pilot’s contribution to safety-of-flight during routine air carrier flight operations and in response to aircraft system failures. To quantify the human’s contribution, crew complement (two-crew, reduced crew, single pilot) was used as the independent variable in a between-subjects design. This paper details the crew’s actions, including decision-making, and responses while dealing with a hydraulic systems leak.

An assessment of reduced crew and single pilot operations in commercial transport aircraft operations

Future reduced crew operations or even single pilot operations for commercial airline and on-demand mobility applications are an active area of research. These changes would reduce the human element and thus, threaten the precept that “a well-trained and well-qualified pilot is the critical center point of aircraft systems safety and an integral safety component of the entire commercial aviation system.” NASA recently completed a pilot-in-the-loop high fidelity motion simulation study in partnership with the Federal Aviation Administration (FAA) attempting to quantify the pilots contribution to flight safety during normal flight and in response to aircraft system failures. Crew complement was used as the experiment independent variable in a between-subjects design. These data show significant increases in workload for single pilot operations, compared to two-crew, with subjective assessments of safety and performance being significantly degraded as well. Nonetheless, in all cases, the pilots were able to overcome the failure mode effects in all crew configurations. These data reflect current-day flight deck equipage and help identify the technologies that may improve two-crew operations and/or possibly enable future reduced crew and/or single pilot operations.

Quantifying pilot contribution to flight safety during dual generator failure

Accident statistics cite flight crew error in over 60% of accidents involving transport category aircraft. Yet, a well-trained and well-qualified pilot is acknowledged as the critical center point of aircraft systems safety and an integral safety component of the entire commercial aviation system. No data currently exists that quantifies the contribution of the flight crew in this role. Neither does data exist for how often the flight crew handles non-normal procedures or system failures on a daily basis in the National Airspace System. A pilot-in-the-loop high fidelity motion simulation study was conducted by the NASA Langley Research Center in partnership with the Federal Aviation Administration (FAA) to evaluate the pilots contribution to flight safety during normal flight and in response to aircraft system failures. Eighteen crews flew various normal and non-normal procedures over a two-day period and their actions were recorded in response to failures. To quantify the humans contribution, crew complement was used as the experiment independent variable in a between-subjects design. Pilot actions and performance when one of the flight crew was unavailable were also recorded for comparison against the nominal two-crew operations. This paper details diversion decisions, perceived safety of flight, workload, time to complete pertinent checklists, and approach and landing results while dealing with a complete loss of electrical generators. Loss of electrical power requires pilots to complete the flight without automation support of autopilots, flight directors, or auto throttles. For reduced crew complements, the additional workload and perceived safety of flight was considered unacceptable.

Biocybernetic Adaptation Strategies: Machine Awareness of Human Engagement for Improved Operational Performance

Human operators interacting with machines or computers continually adapt to the needs of the system ideally resulting in optimal performance. In some cases, however, deteriorated performance is an outcome. Adaptation to the situation is a strength expected of the human operator which is often accomplished by the human through self-regulation of mental state. Adaptation is at the core of the human operator’s activity, and research has demonstrated that the implementation of a feedback loop can enhance this natural skill to improve training and human/machine interaction. Biocybernetic adaptation involves a “loop upon a loop,” which may be visualized as a superimposed loop which senses a physiological signal and influences the operator’s task at some point. Biocybernetic adaptation in, for example, physiologically adaptive automation employs the “steering” sense of “cybernetic,” and serves a transitory adaptive purpose – to better serve the human operator by more fully representing their responses to the system. The adaptation process usually makes use of an assessment of transient cognitive state to steer a functional aspect of a system that is external to the operator’s physiology from which the state assessment is derived. Therefore, the objective of this paper is to detail the structure of biocybernetic systems regarding the level of engagement of interest for adaptive systems, their processing pipeline, and the adaptation strategies employed for training purposes, in an effort to pave the way towards machine awareness of human state for self-regulation and improved operational performance.

Uncertainty in Heart Rate Complexity Metrics caused by R-peak Perturbations

Heart rate complexity (HRC) is a proven metric for gaining insight into human stress and physiological deterioration. To calculate HRC, the detection of the exact instance of when the heart beats, the R-peak, is necessary. Electrocardiogram (ECG) signals can often be corrupted by environmental noise (e.g., from electromagnetic interference, movement artifacts), which can potentially alter the HRC measurement, producing erroneous inputs which feed into decision support models. Current literature has only investigated how HRC is affected by noise when R-peak detection errors occur (false positives and false negatives). However, the numerical methods used to calculate HRC are also sensitive to the specific location of the fiducial point of the R-peak. This raises many questions regarding how this fiducial point is altered by noise, the resulting impact on the measured HRC, and how we can account for noisy HRC measures as inputs into our decision models. This work uses Monte Carlo simulations to systematically add white and pink noise at different permutations of signal-to-noise ratios (SNRs), time segments, sampling rates, and HRC measurements to characterize the influence of noise on the HRC measure by altering the fiducial point of the R-peak. Using the generated information from these simulations provides improved decision processes for system design which address key concerns such as permutation entropy being a more precise, reliable, less biased, and more sensitive measurement for HRC than sample and approximate entropy.Heart rate complexity (HRC) is a proven metric for gaining insight into human stress and physiological deterioration. To calculate HRC, the detection of the exact instance of when the heart beats, the R-peak, is necessary. Electrocardiogram (ECG) signals can often be corrupted by environmental noise (e.g., from electromagnetic interference, movement artifacts), which can potentially alter the HRC measurement, producing erroneous inputs which feed into complex decision models. Current literature has only investigated how HRC is affected by noise when R-peak detection errors occur (false positives and false negatives). However, the numerical methods used to calculate HRC are also sensitive to the specific location of the fiducial point of the R-peak. This raises many questions regarding how this fiducial point is altered by noise, the resulting impact on the measured HRC, and how we can account for noisy HRC measures as inputs into our decision models. This work uses Monte Carlo simulations to systematically add white and pink noise at different permutations of signal-to-noise ratios (SNRs), time segments and HRC measurements to characteristize the influence of noise on the HRC measure by altering the fiducial point of the Rpeak. Using the generated information from these simulations provides improved decision processes for system design which address key concerns such as permutation entropy being a more precise, reliable, less biased, and more sensitive measurement for HRC than sample and approximate entropy.

Repeated Induction of Inattentional Blindness in a Simulated Aviation Environment

The study reported herein is a subset of a larger investigation on the role of automation in the context of the flight deck and used a fixed-based, human-in-the-loop simulator. This portion explored the relationship between automation and inattentional blindness (IB) occurrences in repeated induction using two types of runway incursions directly relevant to primary task performance. Sixty non-pilot participants performed the final five minutes of a landing scenario twice in one of three automation condition: full automation (FA), partial automation (PA), and no automation (NA). The first induction resulted in a 70% detection failure rate and the second induction resulted in a 50% detection failure rate. Detection improved in all conditions. IB group membership (IB vs. Detection) in the FA condition showed the most improvement and rated the Mental Demand and Effort subscales of the NASA-TLX significantly higher for Time 2 compared Time 1. Participants in the FA condition used the experience of IB exposure to reallocate attentional resources and improve task performance. These findings support the role of engagement in attention detriment and the consideration of attentional failure causation to select appropriate mitigation strategies.

Mild Normobaric Hypoxia Exposure for Human-Autonomy System Testing

An experiment investigated the impact of normobaric hypoxia induction on aircraft pilot performance to specifically evaluate the use of hypoxia as a method to induce mild cognitive impairment to explore human-autonomous systems integration opportunities. Results of this exploratory study show that the effect of 15,000 feet simulated altitude did not induce cognitive deficits as indicated by performance on written, computer-based, or simulated flight tasks. However, the subjective data demonstrated increased effort by the human test subject pilots to maintain equivalent performance in a flight simulation task. This study represents current research intended to add to the current knowledge of performance decrement and pilot workload assessment to improve automation support and increase aviation safety.