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Aerospace
Special Issues
Human Factors during Flight Operations
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Human Factors during Flight Operations

A special issue of Aerospace (ISSN 2226-4310). This special issue belongs to the section "Aeronautics".

Deadline for manuscript submissions: closed (15 April 2024) | Viewed by 11057

Special Issue Editors

Dr. Julius Keller

E-Mail Website
Guest Editor
School of Aviation and Transportation Technology, Purdue University, West Lafayette, IN 47907, USA
Interests: fatigue in collegiate aviation; flight training and education; safety management systems
Special Issues, Collections and Topics in MDPI journals
Dr. Dimitrios Ziakkas

E-Mail Website
Guest Editor
School of Aviation and Transportation Technology, Purdue University, West Lafayette, IN 47907, USA
Interests: extended minimum crew operations; implementation of AI in aviation training; single pilot operations; human autonomy teaming
Dr. Abner Flores

E-Mail Website
Guest Editor
School of Aviation and Transportation Technology, Purdue University, West Lafayette, IN 47907, USA
Interests: neuroergonomics-human performance in aviation; artificial intelligence in aviation; human-interactive pilot enhancing performance technologies; extended reality technologies in aviation

Special Issue Information

Dear Colleagues,

It is with great pleasure that we invite you to contribute to this Special Issue, with an emphasis on Human Factors during Flight Operations, and we welcome an international perspective. Aircraft design and reliability, as well as pilots’ education and training, have steadily and significantly improved in the last 25 years. Nevertheless, high-profile accidents still occur, even when the aircraft and related systems are operating adequately. Controlled flight into terrain, runway incursions and excursion accidents, and loss of control in flight are examples of mishaps in which inadequate decision making, poor leadership, faulty human–automation interactions, ineffective communication, and organizational factors are frequently cited as contributing factors. In fact, human factors have been cited as a causal factor in approximately 80% of aircraft accidents.  Further, during the COVID-19 pandemic, mental health issues increased and have garnered attention from key stakeholders. The mental performance of pilots is critical to safe operations. Moreover, due to pilot supply and demand, technological advancements, vigorous research on single-pilot operations, and autonomous vehicle monitoring, we require a fresh perspective on human factors studies. The study of human factors is crucial for aviation safety because it aids in the identification of potential risks and hazards that can lead to errors, accidents, and incidents. By understanding how humans interact with technology, equipment, and the environment, aviation professionals can design systems, procedures, and training programs that reduce the risk of human error and improve overall safety. Overall, aviation is currently at its safest; nevertheless, a vision for the transformation of flight operations is developing.  

This Special Issue offers scholars and aviation professionals an opportunity to present the latest advancements in the development of interventions, technologies, and tools specially designed for the enhancement of human performance. Manuscripts that fit into the following broad categories will be considered:

  • Aviation safety;
  • Safety management;
  • Human–machine interactions;
  • Fatigue identification and management;
  • Evidence-based training;
  • Ergonomics;
  • Aircraft accident investigation;
  • Artificial Intelligence;
  • AR/VR/MR. 

Dr. Julius Keller
Dr. Dimitrios Ziakkas
Dr. Abner Flores
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Aerospace is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (7 papers)

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Research

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21 pages, 343 KiB  
Article
What Do You Need? Information Requirements and Task Analysis of (Future) Advanced Air Mobility Pilots in the Emergency Medical Service
by Dominik Janetzko and Bacem Kacem
Aerospace 2024, 11(3), 197; https://doi.org/10.3390/aerospace11030197 - 29 Feb 2024
Viewed by 987
Abstract
In the domain of Advanced Air Mobility (AAM), Simplified Vehicle Operations (SVOs) promise a reduction in handling complexity and training time for pilots. Designing a usable human–machine interface (HMI) for pilots of SVO-enabled aircraft requires a deep understanding of task and user requirements. [...] Read more.
In the domain of Advanced Air Mobility (AAM), Simplified Vehicle Operations (SVOs) promise a reduction in handling complexity and training time for pilots. Designing a usable human–machine interface (HMI) for pilots of SVO-enabled aircraft requires a deep understanding of task and user requirements. This paper describes the results of two user research methods to gather these requirements. First, a traditional Helicopter Emergency Medical Service (HEMS) mission was examined using a Hierarchical Task Analysis (HTA). The findings were used to formulate a theoretical HTA for a single-piloted electric Vertical Take-Off and Landing (eVTOL) system in such a scenario. In the second step, qualitative interviews with seven subject matter experts (pilots and paramedic support) in HEMS operations produced vital user requirements for HMI development. Key findings emphasize the necessity of a simplified information presentation and collision avoidance support in the HMI. Full article
(This article belongs to the Special Issue Human Factors during Flight Operations)
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14 pages, 1797 KiB  
Article
Air Traffic Controller Fatigue Detection by Applying a Dual-Stream Convolutional Neural Network to the Fusion of Radiotelephony and Facial Data
by Lin Xu, Shanxiu Ma, Zhiyuan Shen and Ying Nan
Aerospace 2024, 11(2), 164; https://doi.org/10.3390/aerospace11020164 - 17 Feb 2024
Viewed by 728
Abstract
The role of air traffic controllers is to direct and manage highly dynamic flights. Their work requires both efficiency and accuracy. Previous studies have shown that fatigue in air traffic controllers can impair their work ability and even threaten flight safety, which makes [...] Read more.
The role of air traffic controllers is to direct and manage highly dynamic flights. Their work requires both efficiency and accuracy. Previous studies have shown that fatigue in air traffic controllers can impair their work ability and even threaten flight safety, which makes it necessary to carry out research into how to optimally detect fatigue in controllers. Compared with single-modality fatigue detection methods, multi-modal detection methods can fully utilize the complementarity between diverse types of information. Considering the negative impacts of contact-based fatigue detection methods on the work performed by air traffic controllers, this paper proposes a novel AF dual-stream convolutional neural network (CNN) architecture that simultaneously extracts controller radio telephony fatigue features and facial fatigue features and performs two-class feature-fusion discrimination. This study designed two independent convolutional processes for facial images and radio telephony data and performed feature-level fusion of the extracted radio telephony and facial image features in the fully connected layer, with the fused features transmitted to the classifier for fatigue state discrimination. The experimental results show that the detection accuracy of radio telephony features under a single modality was 62.88%, the detection accuracy of facial images was 96.0%, and the detection accuracy of the proposed AF dual-stream CNN network architecture reached 98.03% and also converged faster. In summary, a dual-stream network architecture based on facial data and radio telephony data is proposed for fatigue detection that is faster and more accurate than the other methods assessed in this study. Full article
(This article belongs to the Special Issue Human Factors during Flight Operations)
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60 pages, 15901 KiB  
Article
Simulating Flight Crew Workload Settings to Mitigate Fatigue Risk in Flight Operations
by Dajana Bartulović, Sanja Steiner, Dario Fakleš and Martina Mavrin Jeličić
Aerospace 2023, 10(10), 904; https://doi.org/10.3390/aerospace10100904 - 23 Oct 2023
Viewed by 1088
Abstract
In flight operations, the workload settings refer to the shift work, duty time, flight time, number of sectors, rest periods, time of day, duty patterns, number of time-zone transitions, number of consecutive duty days, and changes in the schedule. Workload factors, together with [...] Read more.
In flight operations, the workload settings refer to the shift work, duty time, flight time, number of sectors, rest periods, time of day, duty patterns, number of time-zone transitions, number of consecutive duty days, and changes in the schedule. Workload factors, together with the biological mechanisms (the circadian rhythm, homeostatic sleep pressure, sleep inertia), can lead to the appearance of fatigue. Fatigue affects numerous tasks, such as performing inaccurate flight procedures, missing radio calls, missing or being too slow to pick up system warnings, forgetting or performing routine tasks inaccurately, and others. The focus of this paper is to determine which flight crew workload settings elements impact the appearance of fatigue. The process of collecting data regarding flight crew workload settings and fatigue is conducted on a sample of four airline pilots using an electronic CRD system of standardized chronometric cognitive tests and subjective self-assessment scales. Causal modeling tools of the IBM SPSS Statistics were used to detect correlations among flight crew workload settings, indicators of the subjective perception of fatigue, and measured fatigue indicators. In the final step, a set of simulations was created using simulation tools of the IBM SPSS Statistics to show how modifications of flight crew workload settings, such as modified duty time, number of days off, and others, can impact the level of fatigue. The obtained results can help improve the future planning of flight crew workload set-up and mitigate or prevent the appearance of fatigue in flight operations. Full article
(This article belongs to the Special Issue Human Factors during Flight Operations)
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14 pages, 889 KiB  
Article
Studies on the Relationship between Occupational Stress and Mental Health, Performance, and Job Satisfaction of Chinese Civil Aviation Pilots
by Yanzeng Zhao, Yanlong Wang, Wei Guo, Lin Cheng, Jialu Tong, Ruipeng Ji, Yizhi Zhou, Ziyu Liu and Lijing Wang
Aerospace 2023, 10(10), 896; https://doi.org/10.3390/aerospace10100896 - 20 Oct 2023
Viewed by 1444
Abstract
This research work delves into the potential impact of occupational stress on the mental health, performance, and job satisfaction of civil aviation pilots. To explore this triadic relationship, a battery of six distinct scales was employed, including the Chinese Civil Aviation Pilot Occupational [...] Read more.
This research work delves into the potential impact of occupational stress on the mental health, performance, and job satisfaction of civil aviation pilots. To explore this triadic relationship, a battery of six distinct scales was employed, including the Chinese Civil Aviation Pilot Occupational Stress Scale, the Symptom Check List-90 (SCL-90), the Flight Performance Scale, the Job Satisfaction Scale, the Minnesota Satisfaction Questionnaire (MSQ), and the Simplified Coping Style Questionnaire (SCSQ). A total of 131 valid questionnaires were collected for analysis, yielding a valid response rate of 65.5%. The findings demonstrate a negative correlation between occupational stress experienced by Chinese civil aviation pilots and their mental health, performance, and job satisfaction. Notably, a positive coping style was identified as a moderator in the relationship between occupational stress and flight performance, effectively mitigating the negative impact of stress on flight performance. Similarly, a negative coping style was found to moderate the relationship between occupational stress and job satisfaction, attenuating the adverse effects of occupational stress on job satisfaction. This study underscores the predictive utility of investigating the occupational stress experienced by pilots for understanding their mental health, performance, and job satisfaction. Furthermore, it highlights the potential for adjusting the negative impact of occupational stress on flight performance and job satisfaction through interventions that target pilots’ coping styles. Full article
(This article belongs to the Special Issue Human Factors during Flight Operations)
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42 pages, 7976 KiB  
Article
Correlations among Fatigue Indicators, Subjective Perception of Fatigue, and Workload Settings in Flight Operations
by Dajana Bartulović, Sanja Steiner, Dario Fakleš and Martina Mavrin Jeličić
Aerospace 2023, 10(10), 856; https://doi.org/10.3390/aerospace10100856 - 29 Sep 2023
Viewed by 964
Abstract
Conducting flight operations at the pace of air traffic relies on shift work, overtime work, work at night, work in different and numerous time zones, and unbalanced flight crew schedules. Such working hours and workload settings can cause disturbances of the circadian rhythm [...] Read more.
Conducting flight operations at the pace of air traffic relies on shift work, overtime work, work at night, work in different and numerous time zones, and unbalanced flight crew schedules. Such working hours and workload settings can cause disturbances of the circadian rhythm and sleep disorders among flight crew members; this can result in fatigue and can have an impact on the safety of flight operations. Fatigue impacts many cognitive abilities such as vigilance, memory, spatial orientation, learning, problem solving, and decision making. In aviation, fatigue has been identified as a hazard to the safety of flight operations. This paper describes objectivation methods for data collecting processes regarding flight crew fatigue, using an electronic system of standardized chronometric cognitive tests and subjective self-assessment surveys on the subjective perception of fatigue. The data collected were analyzed using statistical methods to identify and quantify elements that affect the appearance of fatigue. Finally, causal modeling methods were used to determine correlations among the measured flight crew fatigue indicators, the subjective perception of fatigue, and the defined workload settings. The results of this research reveal which elements strongly impact flight crew fatigue. The detected correlations can help define improved measures for the mitigation of fatigue risk in future flight operations. Full article
(This article belongs to the Special Issue Human Factors during Flight Operations)
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18 pages, 3337 KiB  
Article
Risk Analysis of Airplane Upsets in Flight: An Integrated System Framework and Analysis Methodology
by Na Lu and Bin Meng
Aerospace 2023, 10(5), 446; https://doi.org/10.3390/aerospace10050446 - 12 May 2023
Cited by 1 | Viewed by 1399
Abstract
Generally, airplane upsets in flight are considered a precursor to loss of control in flight (LOC-I) accidents, and unfortunately LOC-I is classified as the leading cause of fatal accidents. To further explore the risk factors, causal relationships, and coupling mechanism of airplane upsets, [...] Read more.
Generally, airplane upsets in flight are considered a precursor to loss of control in flight (LOC-I) accidents, and unfortunately LOC-I is classified as the leading cause of fatal accidents. To further explore the risk factors, causal relationships, and coupling mechanism of airplane upsets, this study proposed a risk analysis model integrating the Interpretative Structural Modeling (ISM) and Bayesian Network (BN). Seventeen key risk factors leading to airplane upsets were identified through the analysis of typical accident cases and the literature. The ISM approach was used to construct the multi-level interpretative structural model of airplane upsets, which could reveal the causal relationship among various risk factors and risk propagation paths. Then, taking 286 accident/incident investigation data as training samples, a data-driven BN model was established using machine learning for dependency intensity assessment and inference analysis. The results reveal that the interaction among risk factors of fatal accidents caused by airplane upsets is more significant than that of non-fatal accidents/incidents. Risk factors such as pilot-induced oscillations/airplane-pilot coupling and non-adherence to Standard Operating Procedures (SOPs)/neglect of cross-validation have a significant effect on airplane upsets in flight among seventeen risk factors. Moreover, this study also identifies the most likely set of risk factors that lead to fatal accidents caused by airplane upsets. The research results have an important theoretical significance and application value for preventing airplane upsets risk. Full article
(This article belongs to the Special Issue Human Factors during Flight Operations)
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Review

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20 pages, 1040 KiB  
Review
Natural Language Processing (NLP) in Aviation Safety: Systematic Review of Research and Outlook into the Future
by Chuyang Yang and Chenyu Huang
Aerospace 2023, 10(7), 600; https://doi.org/10.3390/aerospace10070600 - 30 Jun 2023
Cited by 7 | Viewed by 3460
Abstract
Advanced digital data-driven applications have evolved and significantly impacted the transportation sector in recent years. This systematic review examines natural language processing (NLP) approaches applied to aviation safety-related domains. The authors use Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to conduct [...] Read more.
Advanced digital data-driven applications have evolved and significantly impacted the transportation sector in recent years. This systematic review examines natural language processing (NLP) approaches applied to aviation safety-related domains. The authors use Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to conduct this review, and three databases (Web of Science, Scopus, and Transportation Research International Documentation) are screened. Academic articles from the period 2010–2022 are reviewed after applying two rounds of filtering criteria. The sub-domains, including aviation incident/accident reports analysis and air traffic control (ATC) communications, are investigated. The specific NLP approaches, related machine learning algorithms, additional causality models, and the corresponding performance are identified and summarized. In addition, the challenges and limitations of current NLP applications in aviation, such as ambiguity, limited training data, lack of multilingual support, are discussed. Finally, this review uncovers future opportunities to leverage NLP models to facilitate the safety and efficiency of the aviation system. Full article
(This article belongs to the Special Issue Human Factors during Flight Operations)
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