Title: quantitative study whether the flying skills of the pilots who fly transport category aircraft with a completely automated flight decks deteriorate in comparison with pilots who are flying aircraft with conventional non-automated flight decks
This graduate capstone project is written to satisfy the requirements for the master in aeronautical science. A comparison will be made between the flying skills, measured by the stick and rudder skills, of pilots flying transport category aircraft with fully automated cockpits and pilots flying aircraft with conventional non-automated flight decks.
Background of the Problem
Since the beginning of the 1950’s with the design of the jet powered Boeing 707, aircraft engineers have constantly investigated methods and built devices to reduce the workload of the pilots. The introduction of the autopilot decreased the workload significantly in cruise flight, giving the crew the opportunity to rest from flying the aircraft (Wells, 1999). The first autopilots could only maintain altitude and heading. In the mid-seventies the aviation community encountered a complete new technology with auto-throttle; autopilots capable of flying instrument approaches and even making complete automated landings in zero visibility (Wells, 1999). The autopilot also had the capability to make complete unassisted take-offs in limited visibility, leaving the crew with the task of observation and verification of what the autopilot was doing.
By the end of the 1970s, the flight management system was developed and installed in aircraft. The flight management system was linked with the autopilot and could direct the autopilot in different modes, and even change altitudes and headings. This enabled the flight crew to program the whole flight in a computer, and the system is capable of flying the whole flight without any input from the pilots. The only task the pilot has is the taxiing to the correct runway before take-off and the taxiing to the appropriate gate after landing (Wells, 1999).
At the beginning of the 1980’s Airbus and Boeing introduced the cathode ray tubes to depict the information like airspeed, altitude, flight attitude, heading, and vertical speed indication, instead of the conventional gauges showing the information to the flying pilot. Many aircraft had both systems, the cathode ray tubes as primary with the conventional gauges as back-up (Norris, 1999).
In the late 1980’s with the introduction of the Airbus A320 which is equipped with a complete automated flight deck with multiple computers, all the information is depicted on multiple computer screens, not only the flight information but also the engine status, and the relative information from all the on-board systems. The only conventional gauges are the standby instruments, which are only used if the primary computer systems would fail because of a total electrical failure. The current flight deck automation includes: autopilots, flight management systems, electronic flight instrument system, crew alerting and indication system, and the flight control system (Norris 2001).
With the airbus aircrafts, the electronic instrument system, the crew alerting system, and the indication system changed along with the flight control system. The Airbus A320 was the first civil aircraft with a fly-by-wire system as a flight control system (Norris 1999).
The fear that pilots may place too much confidence in the new technology, and rely too intensively on the automatic functions of the aircraft, together with inappropriate and accelerated training could result in reduction in manual flying skills. The concern exists that pilots may no longer be able to control the aircraft in a case of an emergency such as sudden mechanical failure (Veillette, 2006)
Statement of the problem
In this research paper a study will be made whether the flying skills of pilots flying aircraft equipped with automated flight decks has negatively been impacted when they are required to fly the aircraft manually. A comparison will be made whether the flying skills, measured by the stick and rudder skills, of pilots flying transport category aircraft with fully automated cockpits are deteriorated as compared to pilots flying aircraft with conventional flight decks.
Definitions of terms
Autopilot: Also called Automatic Pilot. An automatic flight control system that keeps an aircraft in level flight or on a set course. The human pilot can direct automatic pilots, or the autopilot can be coupled to a radio navigation signal.
Category: With respect to the certification of aircraft, this is a grouping of aircraft based upon intended use or operating limitations. Examples include: Transport, Normal, Utility, Acrobatic, Limited, Restricted, and provisional.
Engine Indicating and Crew alerting system: EICAS. A system on the flight deck which indicates and projects the information to the flight crew about the status of the engines, aircraft systems, and control systems.
Federal Aviation Administration: FAA. A subsidiary of the Department of Transportation, the FAA establishes and enforces the rules and regulations for air travel. The purpose of the FAA is to set the standards of civil aircraft for the public safety.
Federal Aviation Regulations: FAR. These are the rules, regulations, and guidelines that govern the operation of aircraft, airways, and airmen established by the FAA for the safety and operation of civil aircraft.
Flight control system: The device on the flight deck which is manually operated to generate signals which cause the aircraft to climb, dive, or perform coordinated turns.
Flight deck: The area in an aircraft that house all of the occupants who fly the aircraft, along with all the controls used in flight. It includes the flight stations for the pilot, co-pilot, flight engineer, navigator, and radio operator.
Joint Aviation Authority: JAA. A component of the Department of Transportation of the European Union. The JAA establishes rules and regulations for all nations that are part of the European Union.
National Transportation and Safety Board: NTSB. The National Transportation Safety Board is an independent federal agency charged by congress with the investigation of every civil aviation accident in the United States as well as significant accidents in the other modes of transportation – railroad, highway, marine and pipeline – and to issue safety recommendations aimed at preventing accidents.
Throttle: Device on the flight deck to be used to set the power output of the engine.
Flight management system: FMS. A complete instrument system that is connected to the autopilot which is coupled which is coupled with radio navigation and approach equipment. An aircraft with an FMS can be flown in a completely automatic mode.
Gathering accurate information on pilot performance proved challenging. The researcher has assumed that the available information is accurate and reliable. The primary sources used to compile the information are available on the Internet from government and valid private sources. Aircraft accidents are rarely caused by just one event, but are a chain of events leading to an undesired outcome. Because of the sensitivity of the information and the liability issues related to accidents, some information is classified when not beneficial to the cause. The charter of the National Transportation and Safety board is to investigate all civil accidents and publish all findings in an available public report. The reports published by the NTSB offers encouragement that the information is accurate and not censored or misrepresented for propaganda purposes or protection of an individual.
The researcher has limited this project to pilots flying transport category aircraft certified under part 25 of the Federal Aviation Regulations. This ignores the parallel situation that exists with general aviation aircraft that are certified under Part 23 of the federal aviation regulations. This was a deliberate choice, and the opportunity is available for the student of general aviation to perform a similar analysis of those operations.
This study project is limited to pilots certified under the rules of the United States (Federal Aviation Administration) and Europe (Joint Aviation Authority). This study recognizes the fact that many other pilots in the world fly the same equipment, but are not licensed under the FAA or JAA. Those pilots are excluded from the parameters of this study, but are certainly worthy of separate analysis.
REVIEW OF RELEVANT LITERATURE AND RESEARCH
In a variety of domains, the development and introduction of advanced automated systems has led to an increase in efficiency and precision of operations. At the same time, unexpected problems with human-automation interaction related to the “communication with machines rather than operation of machines” (Card, 1983) have been observed. Effective communication with advanced automation technology is becoming increasingly important because these systems are no longer passive tools but, rather, agent-like devices that operate at a high level of autonomy and authority (Billings, 1996).
Advanced automation can initiate actions without immediately preceding or directly related operator input (i.e., autonomy), and it is capable of modulating or overriding user input (i.e., authority). These properties of modern technology impose high attention and knowledge demands on operators, who need to maintain awareness of the automation’s status, behavior, intentions, and limitations in order to efficiently coordinate their activities with the system.
Close observation of human-automation interaction in a variety of domains, particularly aviation (Sarter, 1997) has shown that operators often are unable to anticipate and track automation activities and changes. This results in automation surprises, in which actual system behavior violates operators’ expectations. Automation surprises begin with poor assessments and miscommunications between the automation and the operator(s), which lead to a gap between the operator’s understanding of what the automated systems are set up to do, and how the automated systems are or will be handling the underlying processes. This gap results in crews being surprised at a later time, when the system’s behavior does not match the crew’s expectations. A critical question is whether operators detect unexpected and undesirable process behavior in time to prevent or recover from negative consequences.
The three interrelated factors given rise to the gap between the actual system configuration and activities and the operators’ expectations about automation behavior are:
(a) Poor mental models,
(b) Low system observation potential, and
(c) Highly dynamic and/or non-routine situations (Sarter 1995).
The increasing capabilities and complexity of automated systems create new knowledge demands for people charged with supervising system activities. Operators need to know more about how the system works and how to work the system in a variety of operational contexts (Abbott, 1996). Increasing knowledge demands, coupled with static or decreasing training investments, can easily lead to significant gaps or misconceptions in users’ mental models of the automated systems they manage.
Observation potential refers to the ability of available feedback to actively support operators in monitoring and staying ahead of system activities and transitions. Observation potential is more than mere data availability; it depends on the cognitive work needed to extract meaning from the available data. Automated systems often provide poor or little feedback about their current or future activities (Norman, 1990). As a result, operators have to perform significant cognitive work to infer what the automated systems are doing and what they will do next as operational circumstances change. Low observation potential also impairs long-term learning and gradual improvement of operators’ mental model with experience (Sarter, 1994).
The analysis of automation reveals one more contributing or enabling factor. Automation surprises tend to occur primarily in the context of situations that involve a high degree of dynamism, non-routine elements, or both, or conjunctions that impose high demands on the human’s attention resources and therefore involve a high risk of losing track of system behavior (Sarter, 1994; Woods, 1994).
The high degree of autonomy and authority of modern automated systems, gaps in the operator’s mental model of the automation and its interactions, low observation potential interfaces, and situations with non-routine elements and conjunctions make it difficult for operators to track and anticipate the activities of their automated partners, producing automation surprises.
Diverse and Changing Automation
The properties of automated systems are neither static nor homogeneous. Natural variations in system design exist in the form of systems that implement different automation philosophies or that belong to different generations of automation technology (Billings, 1997). In other words, automation refers to a wide variety of systems that differ with respect to their capabilities and design features. Surprisingly, automation-related research rarely acknowledges the importance of such differences; rather, it operates under the assumption that the word automation refers to a group of homogeneous systems. However, as automated systems change with respect to properties such as authority, autonomy, and observability, the roles of and demands on the people who must work with the automated systems are affected.
This paper presents a measure of pilot-reported automation surprises in order to aid understanding of the impact of evolving technologies on human-automation cooperation. Pilots on one of the most advanced automated aircraft currently in operation, the Airbus A-320, were asked to describe specific cases and experiences with operating the automation on this aircraft. We gathered the resulting corpus of automation surprises in order to learn about possible changes in the nature and circumstances of difficulties with automation on this advanced aircraft as opposed to problems identified in research on earlier generation glass cockpit aircraft. (Glass cockpit refers to the replacement of traditional analog round-dial gauges by CRTs for the presentation of flight-related information (Wiener, 1989)). To better understand why breakdowns in pilot-automation communication occur, we will also ask pilots to describe their strategies for monitoring the status and behavior of automated flight deck systems. Finally, we will discuss pilots’ attitudes toward and experiences with the unique design of flight controls on advanced aircraft.
Evolution and Impact of Automated Systems
Automated systems differ with respect to important properties, such as their level of authority, autonomy, or observability. One recent trend in automation design is an increase in the level of system autonomy and authority. Autonomy refers to the ability of a system to carry out a sequence of actions without requiring immediate pilot input and to execute actions without pilot consent (Woods, 1996)
Such a level of independence is possible because many modern systems can change their behavior in response to input from a variety of sources, including the pilot, a variety of sensors relating information about the aircraft’s location and environment, and pre-designed instructions. This property presents the operator with a challenging task: tracking all the possible sources of input and the consequences of how they combine and interact to affect system status and behavior.
Advanced systems also involve a high level of authority. Such a system is capable of taking over control of the monitored process from human operators if it decides that intervention is warranted based on its perception of the situation and its internal designer-defined criteria (Woods, 1996). A system’s level of authority cannot be completely separated from its level of autonomy. An example of the combination of high authority and autonomy in the aviation domain is the envelope protection function on advanced automated aircraft. Envelope protection refers to the ability of the automation to detect and prevent or recover from predefined unsafe aircraft configurations. In the course of doing so, the automation has the power to limit, alter, or override any pilot input that seems to interfere with the automation’s efforts to prevent or recover from the detected problem.
As levels of system authority and autonomy increase, it becomes more important for humans and machines to communicate their intentions and actions and for people to clearly understand the capabilities and limitations of automated systems. To support communication and coordination, a third trend in automation design may be necessary: improved system observability. Advanced systems need to provide effective feedback to the aircrew in a variety of areas, such as confirmation that the automation has understood the intent of user instructions, clear indications of mode transitions, and a preview of future automation activities.
However, developments in feedback design do not seem to keep pace with the evolution of increasingly powerful agent-like systems. Even on the most advanced flight decks, available feedback does not differ significantly from that presented by earlier automated stems. For example, feedback on the active mode configuration of the flight management system is always presented in the form of cryptic alphanumeric flight mode annunciations (e.g., HDG SEL, SRS, NAV) in some location on the primary flight display. On most aircraft, information about active system targets (what the automated system is trying to accomplish) is not well integrated with related information about automation status and aircraft behavior. Some of the relevant data can be found on the flight control unit or mode control panel located in the glare shield. Others are presented on the various pages of the multifunction control-display unit, and yet a different subset is shown on the primary flight display.
Finally, on the majority of automated aircraft, information concerning the lateral flight path is provided on the moving map display on the horizontal situation indicator, but no analogous display is provided to depict the significant aspects of the future vertical flight path. In those few cases in which the design of cockpit displays and controls has changed in fundamental ways, it is not clear that these changes improve the observability of the overall system.
To summarize, advanced automated systems involve high levels of authority and autonomy. Their resulting agent-like behavior requires increased coordination between human and machine to ensure that the system operator can maintain a high level of awareness of the activities and intentions of the automated system (Billings, 1997). A lack of significant improvements in feedback design, however, seems to have widened the gap between required and available information on automation status and behavior.
Communication and Coordination Breakdowns
Warnings of potential problems with cockpit automation were voiced as early as the late 1970s (Edwards, 1977), and concerns have been fueled ever since by incidents and accidents involving automated aircraft (Sparaco, 1994); pilot reports of difficulties that are experienced during training and line operations (Sarter, 1992); and by the results of empirical research on pilot-automation interaction (Wiener, 1989).
In the past 15 years, one particular class of problems with automation surprises has become a major concern for the aviation industry in that they have contributed to the evolution of incidents and accidents involving modern automated aircraft (Lenorovitz, 1990). In the case of aviation automation, automation surprises are symptomatic of a lack of mode awareness; a misunderstanding of the current and future status and behavior of the automation (Sarter, 1994). A lack of mode awareness, in turn, is the result of various factors, including inadequate feedback on system activities and gaps or misconceptions in pilots’ knowledge and understanding of the automation (Woods, 1995).
Current understanding of these automation surprises is based primarily on the results of studies that focused on an early generation of automated aircraft, such as the B-757/767 (Wiener, 1989) and the B-737-300/400 (Sarter, 1994). These studies indicated that pilots sometimes lose track of automation behavior and experience difficulties with directing the automation, primarily in the context of highly dynamic situations, abnormal situations, or both. The capacity to generalize these findings is limited, however, because these studies employed aircraft that were built by the same manufacturer, were based on the same philosophy of automation, and involved a similar interface design. Automation on more advanced aircraft that were fielded in the late 1980s and early 1990s (e.g., the MD-11, the Airbus A-320, or the B-747-400) differs from earlier systems with respect to properties such as their level of autonomy, authority, coupling, and complexity.
The Airbus A-320 is flown by means of digital controls (fly by wire), the pilot’s input is sent to several flight control computers, which calculate the necessary and allowable adjustments to the flight control surface positions. These computers send their commands to hydraulic actuators, which then move the control surfaces. This design allows for the introduction of new functions such as envelope protection, which prevents the pilot from exceeding certain limits of the flight envelope. In other words, a fly-by-wire design assigns more authority and autonomy to the automation.
The A-320 (as well as other advanced Airbus airplanes) also differs significantly from most other glass cockpit aircraft in terms of the design and operation of its flight controls. Yokes have been replaced by side-sticks that are not cross-coupled (i.e., in manual operations, movement of one side-stick does not lead to parallel synchronized movement of the other side-stick), and the side-sticks do not move when the aircraft is under automatic control. These aircraft also feature a different approach to thrust control and management with a distinct design of the corresponding controls. In manual operations the A-320 thrust levers operate like conventional throttles (i.e., they move freely), and their position corresponds to the amount of thrust commanded by the pilot. When thrust is under automatic control, however, the thrust levers are placed in one of four detent positions (idle, climb, maximum continuous thrust/FLEX takeoff, takeoff/go-around thrust), which define an upper thrust limit. In other words, when auto-thrust is active, the automatic thrust management system is restricted to varying thrust between idle and the maximum allowable thrust associated with the selected detent position, even if that amount of thrust is not sufficient to achieve or maintain pilot automation-demanded speed or altitude targets. The thrust levers do not move in this mode of operation, and thus their position does not inform the pilot about variations in commanded thrust. Instead, indications of commanded and actual thrust as well as other engine parameters are available only on the electronic centralized aircraft monitoring system, which is located in the forward center position of the cockpit.
The distinct design of flight controls on this aircraft (i.e., the uncoupled side-sticks and the nonmoving throttles) has raised concerns about potential negative effects of removing peripheral visual, tactile, and auditory cues, as these may help pilots monitor automated system activity and maintain energy awareness. However, an earlier survey showed that A-320 pilots who have considerable experience flying with these controls do not share this generic concern. They offer a much more differentiated view of the benefits and disadvantages associated with conventional flight controls, uncoupled side-sticks, and nonmoving throttles (Last, 1991).
To provide additional empirically based input to the ongoing debate about different flight control designs and their implications for the important aspect of automation feedback, pilots were asked to report and comment on their experiences with the A-320 flight controls as part of the corpus on automation surprises.
In this research paper a study will be taken to determine whether the flying skills of pilots flying aircraft equipped with automated flight decks has negatively been impacted when they are required to fly the aircraft manually.
A comparison will be made between the flying skills, measured by the stick and rudder skills, of pilots flying transport category aircraft with that of a fully automated cockpit and pilots flying aircraft with conventional non-automated flight decks.
Once the decision is made that the best way to answer the research problem is by means of quantitative research, there are a number of important aspects, specific to quantitative research, that need to be considered. These aspects include some basic terms, sampling, method of data collection, questionnaire design, data capturing and editing, statistical analysis, interpretation and report writing. Each of these aspects applicable for this research will now be discussed.
In this research paper a study will be taken to determine whether the flying skills of pilots flying aircraft equipped with automated flight decks has negatively been impacted when they are required to fly the aircraft manually.
A comparison will be made between the flying skills, measured by the stick and rudder skills, of pilots flying transport category aircraft with full automated cockpits and pilots flying aircraft with conventional flight decks.
Accident statistics cite the flight crew as a primary contributor in over 80 percent of accidents involving transport category airplanes. The introduction of modern flight deck designs, which have automated many piloting tasks, has reduced or eliminated some types of flight crew errors, but other types of errors have been introduced. Several recent accidents and incidents have emphasized continuing difficulties in flight crew interaction with flight deck automation. Other indicators of potential safety problems, such as flight crew reports, training and operational difficulties, research studies, and surveys also point to vulnerabilities in this area.
Purpose of Study
The objective of study is to test the effect of flying skills of pilots flying aircraft equipped with automated flight decks has negatively been impacted when they are required to fly the aircraft manually. A comparison will be made between the flying skills, measured by the stick and rudder skills, of pilots flying transport category aircraft with fully automated cockpits and pilots flying aircraft with conventional flight decks.
Basic Terms &Concepts
One of the first basic terms central to quantitative research is variable. It can be said that a variable is any entity that can take on different values. In the current context, all the observations or measurements that are made on the sampling units will be represented as variables in a data set.
We want to study the flying skills of the pilots, it will be a variable since it can take on different values for different pilots, and if our sampling units are males and female pilots, gender will also be a variable. Another variable is the total flight time per pilot or the number of service years of different individuals. Once the concept of a variable is understood, it is important to be able to distinguish between dependent and independent variables. This is of interest when we are investigating cause-effect relationship. The dependent variable is that entity that depends on, or is caused by one or more other entities, called the independent variables. If we want to see what effect complete automated flight decks produce on the flying skills of the pilots who fly transport category aircraft, the automated flight deck and conventional flight decks are the independent variables and the flying skills are dependent variables.
The purpose of sampling is to select a number of units from a population of units that is under investigation. The success or failure of the research depends on the scientific correctness of the sample. The reason for this is that the sample results can only be generalized to the population if the sampling is done according to certain standards.
Research Approach/ Questionnaire Design
This is the third stage in the research process. In this study, the questionnaire was patterned after the questionnaire designed. The importance of the design of the questionnaire – i.e. length, types of questions, response options and appearance Many things are considered in order to have a “good” questionnaire. The purpose of this Questionnaire is to gather information from pilots as to what issues are important to them in the means of their flight skills manually and automated.
Validity & Reliability
For the research study to be accurate, its findings must be reliable and valid. Reliability means that the findings would be consistently the same if the study were done over again. Validity refers to the truthfulness of findings; if we really measured what we think we measured, or more precisely, what others think we measured.
A study can be reliable but not valid, and it cannot be valid without first being reliable. We cannot assume validity no matter how reliable our measurements are. There are many different threats to validity as well as reliability, but an important early consideration is to ensure we have internal validity. Anything we do to standardize or clarify our measurement instrument to reduce user error will add to our reliability.
Data Collection and Editing
This is the fourth stage in the research process and relates to the actual observations made on the sample units. This may vary from observing some physical or natural phenomenon and recording our findings, to administering a questionnaire by interviewing pilots.
Editing is the fifth stage in the research process and is all about getting the information that have been collected ready for analysis. Since the analysis is usually done on a computer by means of statistical software, the information must be transferred from the questionnaires to digital format that can be read by computer software.
The United States National Aeronautics and Space Administration (NASA) and the Australian Bureau of Air Safety Investigation (BASI) define a “glass cockpit” as a “highly automated flight management system and electronic flight instrument systems (Flight Safety Foundation, 1999)”.Extensive research has been and continues to be implemented in order to ascertain the truths concerning loss of manual flying skills amongst pilots who have become accustomed to modern automated aircraft. The United States FAA commissioned the Oregon State University and Research Integrations, Inc. to compile available evidence concerning this as well as other elements of safety concerns from pilots, scientists, aviation authorities, and the general public. This compilation of research is presented in the Flight Deck Automation Issues website. The results of this study are presented below:
Percentage of Pilots in Agreement
Percentage of Pilots in Disagreement
Pilots who overuse automation will see their flying skills suffer
Pilots who hand-fly part of every trip to upkeep their flying skills
Pilots who are concerned with a possible loss of flying skills due to automation
Pilots who agree with the statement: Automation does not decrease the pilot’s workload
Automation reduces pilot fatigue
Pilots concerned with the reliability of modern automation equipment
(Research Integrations, Incorporated, 2005)
“Advanced avionics may have deleterious effects on flying skills as pilots spend increasing amounts of time in a supervisory/monitoring role rather than flying the aircraft (Department of Transportation: Federal Aviation Administration: Office of Aviation Research, 2004)”.
General Aviation News reports that there is a love of the newfound technology for pilots. They enjoy the ease of operations as compared to conventional aircraft.” Over time, most will tend to find a degradation in basic instrument skills, however, because those “scan” muscles need exercise on round dials to stay sharp (Sclair, 2004)”.
The FAA reports generally safer flight statistics since the inception of the glass cockpit flight management systems (Department of Transportation: Federal Aviation Administration: Office of Aviation Research, 2004).
When aviation accidents do happen, the primary contributing factor is flight crew error. With every conceivable measure taken to ensure safety and minimize accidents, a fail-proof system of flight has yet to be developed (Department of Transportation: Federal Aviation Administration: Office of Aviation Research, 2004).
(Civil Aviation Authority, 2006)
“Industry anecdotal feedback to the CAA has suggested that the manual flying skills of flight crew in highly automated aircraft are deteriorating (Civil Aviation Authority, 2006)”.
“A three-year NASA study of 200 Boeing 757 pilots found that they were concerned about spending too much time staring at computer screens and not enough looking out the windows. They also worried that their basic flying skills would atrophy as they spent more time punching keypads. ‘I was somewhat concerned with the ‘I can’t fly but I can type 80 words per minute’ syndrome,’ said one pilot. Still, about 90% of the pilots saw the glass cockpit as a big step forward (Sullivan, 1990)”.
Mike Gaffney, from the FAA, states: “We have discussed the issue that many insurance companies require FITS training in order to complete that transition from traditional to glass, but is there a time limit that might be voided before they can safely move back to a conventional cockpit and take it into challenging conditions, such as IFR and night flight (Gaffney, 2001 – 2006)”.
The general consensus seems to indicate both a need and a desire to move forward with technological advances in flight management systems. At the risk of potential atrophy of pilot skills, the future will wait for no man. Pilots in training today will have to embrace a more technology-based training platform, even at the cost of basic, conventional skill development. There can only be forward technological advances in the modern aviation world; it is time to embrace it.
Abbott, K. (1996). The interfaces between flight crews and modern flight deck systems
(FAA Human Factors Team Report). Seattle: Federal Aviation Administration.
Bainbridge, L. (1983). Ironies of automation. Automatica, 19, 775-779.
Billings, C.E. (1991). Human-centered aircraft automation: A concept and guidelines
(NASA Tech. Memorandum 103885). Moffett Field, CA: NASA-Ames Research
Billings, C.E. (1996). Aviation automation: The search for a human-centered approach.
Hillsdale, NJ: Erlbaum.
Card, S. K. (1983). The psychology, of human-computer interaction. Hillsdale, NJ:
Carroll, J. M. (1988). Mental models in human-computer interaction. In M. Helander
(Ed.), Handbook of human-computer interaction (pp. 45-65). Amsterdam:
Civil Aviation Authority. (2006, June). Supproting Pilot Performance. Retrieved January 23, 2007, from CAA: http://www.caa.co.uk/default.aspx?categoryid=978;pagetype=90;pageid=6398
Department of Transportation: Federal Aviation Administration: Office of Aviation Research. (2004, October). Final Report:Review of the FITS Program: Program tasks, goals, and pilot training initiatives. Retrieved February 2, 2007, from Report:Review of the FITS Program: Program tasks, goals, and pilot training initiatives: http://www.niar.twsu.edu/newniar/researchlabs/pdf/FITS%20Final%20report.pdf
Edwards, E. (1977). Automation in civil transport aircraft. Applied Ergonomics, 8, 194-
Eldredge, D. (1991). A review and discussion of Flight Management System incidents
reported to the Aviation Safety Reporting System (Battelle Report, prepared for
the Department of Transportation). Columbus, OH: Volpe National Transportation Systems Center.
Flight Safety Foundation. (1999, June – August). Retrieved Feb 2, 2007, from http://126.96.36.199/fsd/fsd_jun_aug99.pdf
Folkerts, H. H. (1994). Pilot performance in automated cockpits: A comparison of
moving and nonmoving thrust levers (NLR Tech. Report 94005 U). Amsterdam:
National Aerospace Laboratory.
Gaffney, M. (2001 – 2006). No Going Back. Retrieved January 21, 2007, from I Fly America Online: http://www.iflyamerica.org/no-going-back.asp
Last, S. (1991). British Airways Airbus A-320 pilots’ autothrust survey (SAE Tech.
Paper 912225). Warrendale, PA: Society of Automotive Engineers.
Lenorovitz, J. M. (1990). Indian A320 crash probe data show crew improperly configured
aircraft. Aviation Week and Space Technology, 132, 84-85.
Moray, N. (1986). Monitoring behavior and supervisory control. Handbook of perception
and human performance (Vol. 2, pp. 40-51). New York: Wiley.
Nisbett, R. E. (1977). Telling more than we can know: Verbal reports on mental
processes. Psychological Review, 84, 231-259.
Norman, D.A. (1990). The “problem” with automation: Inappropriate feedback and
interaction, not “over-automation.” Philosophical Transactions of the Royal
Society of London, B 327, 585-593.
Norris, G., Wagner, M. (1999). Airbus. Osceola: MBI Publishing.
Norris, G., Wagner, M. (2001). Boeing 777 The technological Marvel. Osceola: MBI
Parasuraman, R. (1993). Performance consequences of automation-induced
“complacency.” International Journal of Aviation Psychology, 3, 123.
Research Integrations, Incorporated. (2005, January 24). Flight Deck Automation Issues. Retrieved February 2, 2007, from Flight Deck Automation Issues: http://www.flightdeckautomation.com/fdai.aspx
Sarter, N. B. (1995). “Knowing when to look where”: Attention allocation on advanced
automated flight decks. In R. S. Jensen (Ed.), Proceedings of the 8th International
Symposium on Aviation Psychology (pp. 239-242). San Diego, CA: Academic.
Sarter, N.B. (1992). Pilot interaction with cockpit automation: Operational experiences
with the flight management system. International Journal of Aviation Psychology,
Sarter, N.B. (1994). Pilot interaction with cockpit automation: II. An experimental study
of pilots’ model and awareness of the flight management and guidance system.
International Journal of Aviation Psychology, 4, 1-28.
Sarter, N. B. (1995). “How in the world did we ever get into that mode?” Mode error and
awareness in supervisory control. Human Factors, 37, 5-19.
Sarter, N. B. (1997). Automation surprises. In G. Salvendy (Ed.), Handbook of human
factors and ergonomics (2nd ed., pp. 1926-1943). New York: Wiley.
Sclair, R. (2004, March 5). Glass: Coming to a cockpit near you; One no longer needs the instrument scan of Superman to fly an approach accurately and safely. Retrieved January 23, 2007, from General Aviation News: http://www.generalaviationnews.com/editorial/articledetail.lasso?-token.key=9045;-token.src=column;-nothing
Sparaco, P. (1994). Human factors cited in French A320 crash. Aviation Week and Space
Sullivan, J. M. (1990, March 3). Avionics in the Media. Retrieved January 22, 2007, from The Risk Digest: http://catless.ncl.ac.uk/Risks/9.73.html
Tenney, Y. J. (1995). Pilot opinions on high level flight deck automation issues: Toward
the development of a design philosophy (NASA Contractor Report 4669).
Hampton, VA: NASA Langley Research Center.
Veillette, P. (2005). Threat and error management. Retrieved March 25, 2006 from the
world wide web at
Veillette, P. (2006). Watching and Waning. Retrieved March 25, 2006 from the world
wide web at
Wells, A. (1999). Commercial Aviation Safety (3rd ed.). New-York: McGraw-Hill.
Wickens, C. D. (1992). Engineering psychology and human performance. Columbus,
Wiener, E.L. (1989). Human factors of advanced technology (“glass cockpit”) transport
aircraft (NASA Contractor Report 177528). Moffett Field, CA: NASA-Ames
Woods, D. D. (1996). Decomposing automation: Apparent simplicity, real complexity. Automation technology and human performance (pp. 3-17). Hillsdale, NJ:
Woods, D. D. (1994). Behind human error: Cognitive systems, computers, and hindsight
(State-of-the-Art Report). Dayton, OH: Crew Systems Ergonomic Information and Analysis Center.