Flight Deck Automation Research Articles

AERODROME MAPPING DATA DESIGN DEVELOPMENT APPROACH HIGHLIGHTS

In accordance with the trend in further intellectualization of mapping data design systems, this article deals with the problem of development methods for obtaining aerodrome mapping data more efficient than the existing methods that use manual vectorization on a raster base. Data usage areas were listed, including automated control systems, flight deck automation, simulators and simulation systems. Much attention was given to main aerodrome mapping data design approaches analysis, which shows that existing aerodrome cartographic data obtaining methods lack functionality. A description and basic requirements for an aerodrome mapping data design system, as well as requirements for the data itself, are presented. Additionally, data validation aspects are noted, including those of a taxi route network. Results of the research suggest that computer-aided design methods make it possible to significantly reduce labor intensity and time required to obtain mapping data. A new approach, which consists in using computer-aided design methods for such data, is proposed. Areas in which this approach can provide a significant effect were identified. Methods, algorithms and programs that implement the approach are being developed in context of the new data design system. It will provide a wide range of functions for aerodrome mapping design. General scheme of the system describing its main components was given. An example of aircraft parking elements design as a part of routing network design is provided.

Investigating the impacts of COVID-19 on aviation safety based on occurrences captured through flight data monitoring

The COVID-19 pandemic led to growing concerns about pilots’ proficiency due to the significant decrease in flight operations. The objective of this research is to provide a proactive approach to mitigate potential risks in flight operations associated with the impact of the COVID-19 pandemic using flight data monitoring (FDM). The results demonstrated significant associations between the pandemic impacts and FDM exceedance categories, flight phases and fleets. Manual flying skill decay, lack of practice effects on use of standard operating procedures and knowledge of flight deck automation should be considered by airlines when preparing for the return to normal operations. An FDM Programme allows prediction of the probability and severity of occurrences for developing an effective SMS within an airline. To mitigate the impacts of the pandemic, tailored training sessions must be implemented, and airlines should strive to avoid additional optional procedures where practicable. Practitioner summary: The COVID-19 pandemic has raised concerns regarding pilot proficiency due to lack of practice effects. Results from the Flight Data Monitoring Programme show significant associations between the pandemic impacts and occurrence categories, fleets, and flight phases. FDM can be applied to mitigate the probability and severity of occurrences for airlines developing effective safety management systems. HIGHLIGHTS There is a significant association between the COVID-19 pandemic stages and FDM events in different flight phases, FDM categories, and aircraft types The COVID-19 pandemic led to a significant increase in FDM exceedances, especially for precursors on runway excursion and go-arounds Airlines should carefully plan training sessions for pilots as the disruptions due to the pandemic led to a lack of practice effect in flight operations Reviewing FDM data may have contributions to establish proactive SMS and mitigate COVID-19 impacts to aviation safety

Safe limits, mindful organizing and loss of control in commercial aviation

In commercial aviation, loss of control (LOC) incidents are currently the single biggest cause of accident fatalities. Although LOC incidents typically have multiple causes, inappropriate flight crew responses to unfamiliar conditions are a major contributor. It has been suggested that restricted exposure to unusual aircraft behavior and limited manual flying are partly responsible for this, both of which are aggravated by high levels of flight deck automation. In this paper, we draw on ideas from human-automation interactions, organizational limits, mindful organizing and sensemaking to explore how systems that are very safe by design may subtly undermine mindful organizing, reducing the ability of operators to handle unusual and expected situations. We discuss “the paradox of almost totally safe systems” (Amalberti, 2001) and argue that as systems become safer by design it is increasingly difficult for operators to handle unusual, extreme events, partly due to an erosion of mindful organizing and partly to the limitations of existing training and simulation.

Cognitive pilot-aircraft interface for single-pilot operations

Considering the foreseen expansion of the air transportation system within the next two decades and the opportunities offered by higher levels of automation, Single-Pilot Operations (SPO) are regarded as viable alternatives to conventional two-pilot operations for commercial transport aircraft. In comparison with current operations, SPO require higher cognitive efforts, which potentially result in increased human error rates. This article proposes a novel Cognitive Pilot-Aircraft Interface (CPAI) concept, which introduces adaptive knowledge-based system functionalities to assist single pilots in the accomplishment of mission-essential and safety-critical tasks in modern commercial transport aircraft. The proposed CPAI system implementation is based on real-time detection of the pilot’s physiological and cognitive states, allowing the avoidance of pilot errors and supporting enhanced synergies between the human and the avionics systems. These synergies yield significant improvements in the overall performance and safety levels. A CPAI working process consisting of sensing, estimation and reconfiguration steps is developed to support the assessment of physiological and external conditions, a dynamic allocation of tasks and adaptive alerting. Suitable mathematical models are introduced to estimate the mental demand associated to each piloting task and to assess the pilot cognitive states. Suitably implemented decision logics allow a continuous and optimal adjustment of the automation levels as a function of the estimated cognitive states. Representative numerical simulation test cases provide a preliminary validation of the CPAI concept. In particular, the continuous adaptation of the flight deck's automation successfully maintains the pilot's task load within an optimal range, mitigating the onset of hazardous fatigue levels. It is anticipated that by including suitably designed Psychophysiological-Based Integrity Augmentation (PBIA) functionalities the CPAI system will allow to fulfil the evolving aircraft certification requirements and hence support the implementation of SPO in commercial transport aircraft.

Representing Work for Device Design and Evaluation Using Biclustering

Successful design of technology for safety critical or high-stakes work demands a clear understanding of the work to be supported, a demand not required for many casual-use applications. Methods are needed to ensure the interaction design of safety-critical systems is aligned with the structure of work. We describe a method for representing work needs, the Work Matrix, to guide design and evaluation. A Work Matrix can be input to biclustering algorithms. Biclustering uncovers implicit structure in the Work Matrix, which can provide guidance for design. Our approach should be relevant to analysts and designers of software and automation for demanding work domains. We present our approach using the domain of piloting and flight deck automation to illustrate how biclustering results can provide guidance for interaction design.

Human Performance Risks and Benefits of Adaptive Systems on the Flight Deck

ABSTRACTObjective: Human performance risks and benefits of adaptive systems were identified through a systematic analysis and pilot evaluation of adaptive system component types and characteristics.Background: As flight-deck automation is able to process ever more types of information in sophisticated ways to identify situations, it is becoming more realistic for adaptive systems to adapt behavior based on their own authority.Method: A framework was developed to describe the types and characteristics of adaptive system components and was used to perform a risk–benefit analysis to identify potential issues. Subsequently, eight representative adaptive system storyboards were developed for an evaluation with pilots to augment the analysis results and to explore more detailed issues and potential risk mitigations.Results: Analysis identified the principal drivers of adaptive “triggering conditions” risk as complexity and transparency. It also identified the drivers of adaptations risks and benefits as the task level and the level of control versus information adaptation.Conclusion: Pilots did not seem to distinguish between adaptive automation and normal automation if the rules were simple and obvious; however, their perception of risk increased when the level of complexity and opacity of triggering conditions reached a point where its behavior was perceived as nondeterministic.

Culture and the Safety of Complex Automated Sociotechnical Systems

Sociotechnical systems are becoming more complex and increasingly automated. Although human error is now widely viewed as playing a key role in the majority of system failures, there is an increasing recognition of the oversimplification inherent in such a view. This paper examines mismatches between the procedures and automation technologies of sociotechnical systems and their operators from the viewpoint of human culture and capabilities, with a particular focus on flight deck automation. Following an introduction to culture, its sources, its measurement, and its effects, this paper describes recent theories of thinking and decision making, and the influence of culture on decisions. Problems that are associated with automation are presented and it is concluded that current automation systems perform as very inadequate team members, leaving the human operators or crew unprepared when failure occurs or unusual events arise.

Flight Deck Automation

In our July 2013 article, “Flight Deck Automation: Invaluable Collaborator or Insidious Enabler?” we addressed the problems induced by flight deck automation. In this second of our two-article series, we propose design concepts intended to improve safety by modifying the interface between human operators and the automation they supervise. We provide examples illustrating our vision toward the implementation of a more context-aware system to enable effective communication of intent, goal progression, and limitations between machine functions and human operators.

An Integrative Approach to Understanding Flight Crew Activity

In this paper, we describe an integrative approach to understanding flight crew activity. Our approach combines contemporary innovations in cognitive science theory with a new suite of methods for measuring, analyzing, and visualizing the activities of commercial airline flight crews in interaction with the complex automated systems found on the modern flight deck. Our unit of analysis is the multiparty, multimodal activity system. We installed a variety of recording devices in high-fidelity flight simulators to produce rich, multistream time-series data sets. The complexity of such data sets and the need for manual coding of high-level events make large-scale analysis prohibitively expensive. We break through this analysis bottleneck by using our newly developed integrated software system called ChronoViz, which supports visualization and analysis of multiple sources of time-coded data, including multiple sources of high-definition video, simulation data, transcript data, paper notes, and eye gaze data. Four examples of flight crew activity serve to illustrate the methods, the theory, and the kinds of findings that are now possible in the study of flight crew interaction with flight deck automation.

Automation, Task, and Context Features

Human–automation interaction (HAI) takes place in virtually every high-technology domain under a variety of operational conditions. Because operators make HAI decisions such as which mode to use, and when to engage, disengage, monitor, or cross-check automation, it is important to understand their perceptions of how system and situational characteristics affect their interaction with automation. The objective of this study was to examine how systematic variations of automation interface, task and context features influence professional pilots’ judgments of HAI situations. Pilots received descriptions of crews interacting with flight deck automation in specific situations and were asked to rate cognitive demands and predict behaviors. Results reflect a complex interplay among automation features, task, and context. Automation features influenced judgments of workload, task management, and potential for automation-related errors; however, the impact of automation on situation awareness seems to be moderated by task features. Unanticipated tasks had broader effects on pilots’ judgments than operational stressors. Results suggest that although changes to automated systems may be small in technical terms, their cognitive and behavioral impact on operators may be significant. Performance effects of automation changes in aviation as well as other domains need to be addressed with reference to task characteristics and situational demands.

Using neural networks to assess flight deck human–automation interaction

The increased complexity and interconnectivity of flight deck automation has made the prediction of human–automation interaction (HAI) difficult and has resulted in a number of accidents and incidents. There is a need to develop objective and robust methods by which the changes in HAI brought about by the introduction of new automation into the flight deck could be predicted and assessed prior to implementation and without use of extensive simulation. This paper presents a method to model a parametrization of flight deck automation known as HART and link it to HAI consequences using a backpropagation neural network approach. The transformation of the HART into a computational model suitable for modeling as a neural network is described. To test and train the network data were collected from 40 airline pilots for six HAI consequences based on one scenario family consisting of a baseline and four variants. For a binary classification of HAI consequences, the neural network successfully classified 62–78.5% depending on the consequence. The results were verified using a decision tree analysis.

The Multimodal Evaluation Module: Design and Validation of a Model-Based Tool to Predict Pilot Noticing of Multimodal Information on the Flight Deck

Flight decks present a great deal of information to pilots, much of it through the visual modality. As new automation and displays are included on the flight deck, including information such as spacing from a lead aircraft, wake vortex displays, and datalink, a text-based messaging system for communication with air traffic control, there is a real concern that these displays can over-burden a pilot’s already-challenged visual system. Auditory, tactile, or redundant modality displays are potential alternatives to yet another visual display. As design concepts are being developed for these new flight deck systems, it is necessary to identify their predicted effects on pilot performance. This paper describes the development and validation of a model-based tool to assist flight deck automation designers and human performance specialists in selecting information presentation modalities that best support pilot performance.

The automation design advisor tool (ADAT): Development and validation of a model‐based tool to support flight deck automation design for nextgen operations

AbstractNextGen aviation will require an even greater reliance on automation than current‐day operations. Therefore, systems with problems in human–automation interaction must be identified and resolved early, well before they are introduced into operation. This paper describes a research and software development effort to build a prototype automation design advisor tool (ADAT) for flight deck automation. This tool uses models of human performance to identify perceptual, cognitive, and action‐related inefficiencies in the design of flight management systems. Aviation designers can use the tool to evaluate and compare potential flight deck automation designs and to identify potential human–automation interaction concerns. Designers can compare different flight management systems in terms of specific features and their ability to support pilot performance. ADAT provides specific, research‐based guidance for resolving problematic design issues. It was specifically designed to be flexible enough for both current‐day technologies and revolutionary NextGen designs. © 2012 Wiley Periodicals, Inc.

Framing the Design, Evaluation, and Certification Process for NextGen Technologies and Procedures: Automation Roles and Responsibilities

To address the foreseeable safety and environmental issues associated with the projected increase in air traffic, an overhaul of the existing air traffic management system, referred to as NextGen, is underway. To support NextGen capabilities, a system of new technologies and procedures will replace or be integrated with current technologies and procedures. This overhaul will, no doubt, change a pilot’s roles and responsibilities, in addition to challenging their existing and future interactions with flight deck automation. To address these challenges, current efforts are being made to develop taxonomies, guidelines, and recommendation that aid with designing, evaluating, and certifying NextGen technologies and procedures. The specific focus for these products is on mitigating pilot error that results from the poor design and integration of NextGen technologies and procedures. The goal of the proposed panel will be to introduce these products, and gain insight and receive feedback from the audience on thei...

The Flight Crew and Automation

"Automation is the allocation of functions to machines that would otherwise be allocated to humans" (Funk et al, 1999). Automation on the flight deck has continued to grow throughout the years, with each new generation of air transport aircraft containing more automation than the last. As flight deck automation progresses at an increasingly rapid rate, the interaction between the pilot and automation will become increasingly more complex. These advances in automation have helped to greatly improve the utility of aircraft, allowing them to do things once thought impossible, such as landing in zero-zero conditions, near full-automated take-offs, and optimizing fuel efficiency. Flight deck automation has brought improvements to the flight deck, but it has also increased the potential for errors in the essential interactions between the automated systems and the human flight crew. The main concern regarding automation on the flight deck is the flight crew losing situational awareness. Other concerns include: loss of manual skill, overconfidence in automation, and difficulty in predicting and monitoring what the automation is doing or will do. There exists a real need to eliminate or mitigate these problems, which pose a significant threat to safety.

Sharing the Burden of Flight Deck Automation Training

Flight deck automation has generated new training requirements, most of which have been absorbed by in-house airline training, in particular, aircraft transition training. This leaves little room for learning about how human roles have shifted in automated cockpits or how the distinction between technical and nontechnical skills has become blurred when managing the flight path of an automated aircraft. This article explores how overall pilot training quality, efficiency, and effectiveness would benefit from pulling automation training forward into the pilot training curriculum, reducing the burden carried mainly by transition training today. This article examines various stages of pilot training (including ab initio, multicrew cooperation, and crew resource management training) and lays out the opportunities and obstacles they contain for the integration of flight deck automation. In conclusion, airlines themselves can play a constructive role by specifying what kinds of automation learning requirements earlier pilot training stages should cover, and by sharing their automation philosophies and actively taking part in the design of the preairline training. Such participation from an airline can help achieve appropriate knowledge and attitudes toward automation among its future pilots.

Flight Deck Automation issues

Although flight deck automation has been well received by pilots and by the aviation industry, many automation human factors issues have been raised. In this study, we surveyed a wide variety of sources, including pilots and other aviation experts; accident reports; incident reports; documentation on other studies of incident reports; and documentation on experiments, surveys, and other studies to identify and compile evidence related to 92 flight deck automation issues. We created a World Wide Web site (http://flightdeck.ie.orst.edu/) to make this information available to the aviation research, development, manufacturing, operational, and regulatory communities.

National Culture and Flight Deck Automation: Results of a Multination Survey

Attitudes regarding flight deck automation were surveyed in a sample of 5,879 airline pilots from 12 nations. The average difference in endorsement levels across 11 items for pilots flying automated aircraft in 12 nations was 53%, reflecting significant national differences in attitudes on all items, with the largest differences observed for preference and enthusiasm for automation. The range of agreement across nations was on average four times larger than the range of agreement across different airlines within the same nation, and roughly six times larger than the range across pilots of standard and pilots of automated aircraft. Patterns of response are described in terms of dimensions of national culture. Implications of the results for development of safety cultures and culturally sensitive training are discussed.

A Functional Model of Flightdeck Agenda Management

Our research represents an effort to understand and facilitate the management of flightdeck activities by pilots. We developed a preliminary, normative theory of Cockpit Task Management (CTM) and from it defined an error taxonomy. Based on analyses using this error taxonomy we found CTM errors in 76 (23 per cent) of 324 aircraft accident reports and 231 (49 per cent) of 470 aircraft incident reports. Concluding that CTM is a significant factor in flight safety and recognizing the need to broaden as well as refine the concept, we developed a model of Agenda Management, which includes management not only of tasks, but goals, functions, actor assignments, and resource allocations as well. Major components of the functional model include maintaining situation awareness, managing goals (recognizing, inferring, and prioritizing), managing functions (activating, assessing status, and prioritizing), assigning actors (pilots and flightdeck automation) to functions, and allocating resources (such as displays and controls) to functions.

A Laboratory Glass-Cockpit Flight Simulator for Automation and Communications Research

A laboratory glass-cockpit flight simulator supporting research on advanced commercial flight deck and Air Traffic Control (ATC) automation and communication interfaces has been developed at the Aviation Operations Branch at the NASA Ames Research Center. This system provides independent and integrated flight and ATC simulator stations, party line voice and datalink communications, along with video and audio monitoring and recording capabilities. Over the last several years, it has been used to support the investigation of flight human factors research issues involving: communication modality; message content and length; graphical versus textual presentation of information, and human accountability for automation. This paper updates the status of this simulator, describing new functionality in the areas of flight management system, EICAS display, and electronic checklist integration. It also provides an overview of several experiments performed using this simulator, including their application areas and results. Finally future enhancements to its ATC (integration of CTAS software) and flight deck (full crew operations) functionality are described.