73 research outputs found

    Human performance in air traffic control

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    Air Traffic Controllers (ATCOs) are responsible for the safety and efficiency of all air traffic. It is essential that controllers maintain a consistently high standard of human performance in order to maintain flight safety. Knowledge of human factor influences on controller performance is critical to understand and mitigate threats to performance. Previous research has largely focused on the association between single factors and performance, which has resulted in a comprehensive understanding of single factor influences. In current control environments however, the residual threats for incidents often result from the interaction of multiple human factors and the resulting cumulative impact on performance. This thesis describes a set of studies that investigate the relationship between multiple, co-occurring factors, and the association with human performance. Findings contribute further understanding of multifactor combinations and associations with human performance, and provide novel and practical recommendations for the mitigation of multifactor influences on controller performance. A literature review, incident report analysis and survey of air traffic professionals confirmed that a majority of research approaches were fundamentally single-factor in nature, which is out of step with real air traffic management (ATM) contexts. In addition, findings confirmed that multiple factors co-occur in an air traffic control (ATC) environment, and are associated with controller performance. An off-line experiment using students as participants investigated the relationship between a set of human factors and the association with performance. Results indicate that several factors known to be associated with controller performance do co-vary and factors may interact to produce a cumulative Influence on performance. An interview study with en-route controllers contributed to an understanding of mitigation strategies of multifactor influences. The research presented in this thesis has contributed findings that have both theoretical and practical implications. This research has addressed long-standing gaps within human performance literature and contributed new understanding to the complex field of human performance in air traffic control. Findings suggest that factors do co-occur in ATC, and interact to negatively influence performance, pushing controllers to the edge of performance. This research argues for a more ecologically valid investigation of real-world systems using multiple factors rather than the traditional one or two-factor paradigms. In addition, this research investigation has contributed novel understanding of mechanisms which may mitigate multifactor influences and has developed practical recommendations for aviation personnel that may be used to support performance, thereby preventing performance decline, with important implications for maintaining and improving safety within the ATC domain

    Human performance in air traffic control

    Get PDF
    Air Traffic Controllers (ATCOs) are responsible for the safety and efficiency of all air traffic. It is essential that controllers maintain a consistently high standard of human performance in order to maintain flight safety. Knowledge of human factor influences on controller performance is critical to understand and mitigate threats to performance. Previous research has largely focused on the association between single factors and performance, which has resulted in a comprehensive understanding of single factor influences. In current control environments however, the residual threats for incidents often result from the interaction of multiple human factors and the resulting cumulative impact on performance. This thesis describes a set of studies that investigate the relationship between multiple, co-occurring factors, and the association with human performance. Findings contribute further understanding of multifactor combinations and associations with human performance, and provide novel and practical recommendations for the mitigation of multifactor influences on controller performance. A literature review, incident report analysis and survey of air traffic professionals confirmed that a majority of research approaches were fundamentally single-factor in nature, which is out of step with real air traffic management (ATM) contexts. In addition, findings confirmed that multiple factors co-occur in an air traffic control (ATC) environment, and are associated with controller performance. An off-line experiment using students as participants investigated the relationship between a set of human factors and the association with performance. Results indicate that several factors known to be associated with controller performance do co-vary and factors may interact to produce a cumulative Influence on performance. An interview study with en-route controllers contributed to an understanding of mitigation strategies of multifactor influences. The research presented in this thesis has contributed findings that have both theoretical and practical implications. This research has addressed long-standing gaps within human performance literature and contributed new understanding to the complex field of human performance in air traffic control. Findings suggest that factors do co-occur in ATC, and interact to negatively influence performance, pushing controllers to the edge of performance. This research argues for a more ecologically valid investigation of real-world systems using multiple factors rather than the traditional one or two-factor paradigms. In addition, this research investigation has contributed novel understanding of mechanisms which may mitigate multifactor influences and has developed practical recommendations for aviation personnel that may be used to support performance, thereby preventing performance decline, with important implications for maintaining and improving safety within the ATC domain

    Methods for Examining Possible Effects of En Route Automation Modernization (ERAM) on Controller Performance

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    The Federal Aviation Administration is developing the En Route Automation Modernization (ERAM) system to replace the legacy en route air traffic control automation system consisting of the Host Computer System, the Display System Replacement (DSR), and the User Request Evaluation Tool (URET). This technical note provides an analysis of major areas where new ERAM features may affect how controllers do their jobs. We describe test methodologies for examining these effects and corresponding metrics. Our analysis examines the following categories of ERAM changes: (a) backup and redundancy capabilities; (b) Areas of Interest (AOIs) that increase flight data capabilities in ERAM; (c) differences between the legacy system and ERAM user interfaces (UIs); (d) the ERAM tracker; and (e) safety alerts. We also discuss two recommended test activities: a usage characteristics assessment and human-in-the loop baseline simulations

    Aerospace medicine and biology: A continuing bibliography with indexes (supplement 407)

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    This bibliography lists 289 reports, articles and other documents announced in the NASA Scientific and Technical Information System during Nov. 1995. Subject coverage includes: aerospace medicine and physiology, life support systems and man/system technology, protective clothing, exobiology and extraterrestrial life, planetary biology, and flight crew behavior and performance

    Human Factors:Sustainable life and mobility

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    Survey of Human Models for Verification of Human-Machine Systems

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    We survey the landscape of human operator modeling ranging from the early cognitive models developed in artificial intelligence to more recent formal task models developed for model-checking of human machine interactions. We review human performance modeling and human factors studies in the context of aviation, and models of how the pilot interacts with automation in the cockpit. The purpose of the survey is to assess the applicability of available state-of-the-art models of the human operators for the design, verification and validation of future safety-critical aviation systems that exhibit higher-level of autonomy, but still require human operators in the loop. These systems include the single-pilot aircraft and NextGen air traffic management. We discuss the gaps in existing models and propose future research to address them
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