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All Experiments 24 resources found.


  1.  
  2. Source: Barbato, G. (1999). Lessons learned: Integrating voice recognition and automation target cueing symbology for fighter attack. In R.S. Jensen, B. Cox, J.D. Callister, & R. Lavis (Eds.), Proceedings of the 10th International Symposium on Aviation Psychology, 203-207. Columbus, OH: The Ohio State University.
    Source Type:   Experiment
    Synopsis: "Automatic target cueing and pilot voice recognition and automatic target cueing were integrated into a single-seat fighter cockpit simulator and were evaluated. Pilots were required to fly a pre-planned route to an airfield, where they identified and designated for attack, six tanker aircraft from a group of fifteen aircraft that were parked on the airfield. During navigation and weapon delivery segments of the mission, simulated Airborne Warning and control directed the pilots to: 1) modify their flight route, 2) change radio frequencies, 3) respond to various tasks and instructions, and 4) attack the airfield. During half of the data collection sessions, data input tasks were performed manually by the pilots using an "upfront" keypad; during the other half of the sessions, data input was accomplished by voice. Additional independent variables were: 1) auditory interference—the number of communications requiring pilot response, and 2) maintaining flight altitude workload—maintain altitude at either 300 feet or 1000 feet above ground level, which was a way to induce workload. Objective measures of performance for data input (speed and accuracy) and for aircraft control (deviations from commanded course, airspeed and altitude) were collected while pilots navigated along the flight route. Objective measures collected during ground attack included speed of target designation, total number of targets correctly designated, and standoff distance from the airfield at target designation. … The overall objective of this experiment was to address this operational context issue by: 1) measuring how the use of voice control influenced the pilot’s ability to multitask in a high task load environment, 2) investigating potential interference between voice control and other vocal communication tasks, 3) determining how voice control could influence mission effectiveness in a simulated air interdiction mission, and 4) assessing the utility of voice control when used in conjunction with automatic target cueing symbology."
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  3.  
  4. Source: Beringer, D.B. (1997). Automation Effects in General Aviation: Pilot Responses to Autopilot Failures and Alarms. In R.S. Jensen & L. Rakovan (Eds.), Proceedings of the 9th International Symposium on Aviation Psychology. Columbus, OH: The Ohio State University.
    Source Type:   Experiment
    Synopsis: "This study examined four malfunctions of the autopilot; two relatively obvious (runway pitch-trim down, runaway roll servo) and two comparatively subtle (failed attitude indicator, pitch sensor drift down), and the effect of an auditory warning. ... The study ... was intended to explore some of the more serious and more subtle malfunctions that did have a moderate probability of causing the termination of the flight. ... Pilots were obtained from the local area who were instrument rated and had experience with complex aircraft and autopilot systems. ... the sample contained 22 men and 2 women. ... Data were collected in the Advanced General Aviation Research Simulator (AGARS), configured as a Piper Malibu was simulated Bendix/King avionics (KAP-150 autopilot), in the FAA Civil Aeromedical Institute Human Factors Research Laboratory. Simulation software, running on Silicon Graphics platforms, approximated the behavior of the Malibu. ... Pilots participated in an experimental session lasting between 2.5 and 3 hours.The first hours consisted of experiment-related paperwork and fmilarization trining activities ... The second half of the session was used to collect performance data for the four malfunction conditions. A round-robin instrument clearance was flown in the Oklahoma city (OKC) area in IFR conditions between textured cloud layers. ... Pilots were required to interact with ATC, fly vectors, track inbound to two VOR stations, and fly a fully-coupled ILS approach, flying as much of the course on autopilot as possible. ... The session concluded with an autopilot experience questionnaire and interview."
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  5.  
  6. Source: Beringer, D.B., & Harris, H.C., Jr. (1999). Automation in general aviation: Two studies of pilot responses to autopilot malfunctions. International Journal of Aviation Psychology, 9(2), 155-174. Lawrence Erlbaum Associates.
    Source Type:   Experiment
    Synopsis: "The focus of our research, in support of Aircraft Certification, was the responses of pilots to overt and subtle AP malfunctions and the factors influencing the speed and the selection of those pilot responses. Two studies were conducted, each examining four AP or AP-influencing system malfunctions, including those producing obvious and immediate effects and those producing more subtle and less-direct effects. The intent was to determine how a sample representative of average GA pilots would respond to AP malfunctions and how those responses would compare with the times specified in the present certification procedures." (page 158) ... "Study 1 examined 4 automation-related malfunctions (runaway pitch trim up, roll servo failure, roll sensor failure, pitch drift up) and subsequent pilot responses. Study 2 examined 4 additional malfunctions, 2 more immediately obvious (runaway pitch trim down, runaway roll servo) and 2 more subtle (failed attitude indicator, pitch sensor drift down) than those in Study 1, and the effect of an auditory warning. Data collection was performed in the Civil Aeromedical Institute’s Advanced General Aviation Research Simulator, configured as a Piper Malibu. Results suggest that maladaptive responses to some of these failures may, in a significant percentage of cases. lead to significant altitude loss, overstress of the airframe, disorientation of the pilot, or destruction of the aircraft. Percentages of successful recoveries, detection and correction times, and related indexes of performance are discussed in the context of malfunction type, flight profile, and auditory alerts." (page 155)
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  7.  
  8. Source: Edwards, R.E., Tolin, P., & Jonsen, G.L. (1982). Pilot Visual Behavior as a Function of Navigation and Flight Control Modes in the Boeing 757/767. In Proceedings of the 26th Annual Meeting of the Human Factors and Ergonomic Society, 441-445.
    Source Type:   Experiment
    Synopsis: "This report presents data obtained from two line-oriented simulations conducted in the Boeing 757/767 simulators. The purpose of these simulations was to assess the impact of two navigation- and two flight control modes on pilot visual behavior during an entire flight, from takeoff to touchdown."
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  9.  
  10. Source: Inagaki, T., Takae, Y., & Moray, N. (1999). Automation and human interface for takeoff safety. In R.S. Jensen, B. Cox, J.D. Callister, & R. Lavis (Eds.), Proceedings of the 10th International Symposium on Aviation Psychology, 402-407. Columbus, OH: The Ohio State University.
    Source Type:   Experiment
    Synopsis: "This paper argues how Go/NoGo decision-making may be supported by human-interface design or by automation. It is shown experimentally that the human-interface with Go/Abort messages is effective for a human to make correct Go/NoGo decisions. It is also shown that there is still room for an automated system to improve takeoff safety in time-critical situations."
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  11.  
  12. Source: Johnson, E.N. & Pritchett, A.R. (1995). Experimental Study Of Vertical Flight Path Mode Awareness. Cambridge, MA: Massachusetts Institute of Technology, Department of Aeronautics and Astronautics.
    Source Type:   Experiment
    Synopsis: "An experimental simulator study was run to test pilot deception of an error in autopilot mode selection. Active airline air crew were asked to fly landing approaches by commanding the 'Flight Path Angle' mode while monitoring the approach with both a Head Up Display and Head Down Displays. During one approach, the 'Vertical Speed' mode was intentionally triggered by an experimenter instead, causing a high rate of descent below the intended glide path. Of the 12 pilots, 10 were unable to detect the high descent rate prior to significant glide path deviation."
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  13.  
  14. Source: Lin, H.X. & Salvendy, G. (2000). Warning effect on human error reduction. International Journal of Cognitive Ergonomics, 4(2), 145-161.
    Source Type:   Experiment
    Synopsis: "In this study, we test whether warnings reduce human error by helping participants to transit from lower performance level to higher performance level. In this study, warnings are those that indicate possible unfavorable outcomes but do not include knowledge of how to perform a task. These warnings are a specific class of warnings and not inclusive of other kinds of warnings that may inform, instruct, and give direct general and specific information. Warnings in this study are not hazard warnings as they are usually investigated in warnings research. More general discussion of warnings can be found in Ayres et al. (1989). If warnings reduce human error by helping participants transit from lower performance level to higher performance level, participants who have high conceptual knowledge level will benefit more from such warnings than participants who have low conceptual knowledge level. This is because participants have to know how to respond to these warnings after they transit to a higher performance level. Because high knowledge participants have more knowledge than low knowledge participants, high knowledge participants know better how to respond to such warnings than low knowledge participants. However, this does not necessarily mean that such warnings reduce more absolute numbers of errors for high knowledge participants than for low knowledge participants. Without warnings, high knowledge participants may make fewer errors than low knowledge participants. With warnings, we would expect that high knowledge participants’ relative human error reduction due to participants’ use of warnings will be higher than that of low knowledge participants."
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  15.  
  16. Source: Lozito, S., McGann, A., & Corker, K. (Undated). Data link air traffic control and flight deck environments: Experiment in flight crew performance.
    Source Type:   Experiment
    Synopsis: "This report describes an experiment undertaken in a full mission simulation environment to investigate the performance impact of, and human/system response to, data-linked Air Traffic Control (ATC) and automated flight deck operations. Subjects were twenty pilots (ten crews) from a major United States air carrier. Crews flew the Advanced Concepts Flight Simulator (ACFS), a generic 'glass cockpit' simulator at NASA Ames. The method of data link used was similar to the data link implementation plans for a next-generation aircraft, and included the capability to review ATC messages and directly enter ATC clearance information into the aircraft systems. Each crew flew experimental scenarios, in which data reflecting communication timing, errors and clarifications, and procedures were collected."
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  17.  
  18. Source: Mosier, K.L., Skitka, L.J., Heers, S., & Burdick, M. (1997). Automation bias: Decision making and performance in high-tech cockpits. International Journal of Aviation Psychology, 8(1), 47-63. Lawrence Erlbaum Associates.
    Source Type:   Experiment
    Synopsis: "This study was designed to investigate automation bias, a recently documented factor in the use of automated aids and decision support systems. The term refers to omission and commission errors resulting from the use of automated cues as a heuristic replacement for vigilant information seeking and processing. Glass-cockpit pilots flew flight scenarios involving automation events or opportunities for automation-related omission and commission errors. Although experimentally manipulated accountability demands did not significantly impact performance, post hoc analyses revealed that those pilots who reported an internalized perception of ‘accountability’ for their performance and strategies of interaction with the automation were significantly more likely to double-check automated functioning against other cues and less likely to commit errors than those who did not share this perception. Pilots were also likely to erroneously ‘remember’ the presence of expected cues when describing their decision-making processes."
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  19.  
  20. Source: Mumaw, R.J., Sarter, N.B., & Wickens, C.D. (2001). Analysis of Pilots' Monitoring and Performance on an Automated Flight Deck. In Proceedings of the 11th International Symposium on Aviation Psychology. Columbus, OH: The Ohio State University..
    Source Type:   Experiment
    Synopsis: "In order to understand the role of pilot monitoring in the loss of mode awareness on automated flight decks, we studied 20 Boeing 747-400 line pilots in a simulated flight. We developed a set of scenario events that created challenges to monitoring. We measured automation use, eye fixations, and pilot mental models...We recruited twenty 747-400 line pilots (10 Captains and 10 First Officers; all male) from two U.S. airlines. Ages ranged from 45-59, with a mean age of 53.3. Pilots had between 100 and 9000 hours on the 747-400 (mean=2600; SD=2100), and they had a minimum of 1000 hours total of glass cockpit experience. Pilots were not paid for their participation...The study was carried out in a 747-400 fixed-base simulator. Each pilot’s front window view covered 45° horizontally and 34° vertically, with a 2° look-down angle. Pilots were encouraged to use flight deck automation (i.e., to not fly manually) until they descended to about 5000 ft, and then a visual approach." "
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  21.  
  22. Source: Muthard, E.K. & Wickens, C.D. (2003). Factors That Mediate Flight Plan Monitoring and Errors in Plan Revision: An Examination of Planning Under Automated Conditions. In Proceedings of the 12th International Symposium on Aviation Psychology, 857-62.
    Source Type:   Experiment
    Synopsis: "An experiment was conducted to explore the effects of automation and task loading on aviation plan monitoring and errors in plan revision. Pilots were asked to select one of two flight paths that traversed through hazardous airspace and to then monitor the safety of the path by seeking and reporting changes in dynamic traffic aircraft and weather systems. Following change detection, pilots were given the opportunity to revise their flight plan as a result of the changes. Attention guidance automation, which was reliable for plan selection, but failed to highlight a critical change that threatened safety after plan selection, was present on half of trials. Automation improved planning accuracy and confidence in high workload conditions. However, in nearly one third of trials, pilots failed to revise the flight plans as a result of a change, and were more likely to do so with imperfect automation in high workload."
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  23.  
  24. Source: Muthard, E.K. & Wickens, C.D. (August 2002). Factors That Mediate Flight Plan Monitoring and Errors in Plan Revision: An Examination of Planning Under Automated Conditions. Nasa Technical Report AFHD-02-11/NASA-02-8. Moffett Field, CA: NASA Ames Research Center.
    Source Type:   Experiment
    Synopsis: "The present experiment sought to explore the effects of automation on plan monitoring and errors in plan revision. Pilots were asked to select one of two flight paths that traversed through hazardous airspace with the aid of attention guidance automation, then monitor the safety of this plan by seeking and reporting changes in dynamic traffic aircraft and weather systems. In one-fourth of trials, an experimenter-induced change threatened the safety of the chosen flight path, and pilots should have optimally revised their plan as a result. In these trials, the automation always failed to highlight this hazard, despite its increase in both its importance to the planning task and its risk to the safety of the flight plan. A secondary loading task was added on all trials. Automation aided plan selection accuracy and secondary task performance. Pilots were poor at plan monitoring, detecting only 30.5% of changes, which is substantially less than that found in a similar, though less demanding version of this experiment. Changes that were relevant to the planning task were detected more quickly than irrelevant changes, and changes to highlighted hazards were more accurately detected than those to non-highlighted hazards. Pilots committed plan continuation errors on nearly one-third of trials, and were more likely to do so under the imperfect automation condition than with no aid present. A relationship between the likelihood of committing a plan continuation error and performance in detecting the change that threatened the safety of the flight path was also found, showing that, in those trials where pilots failed to properly revise a plan, detection of the safety-threatening change was also poorer."
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  25.  
  26. Source: Petridis, R.S., Lyall, E.A., & Robideau, R.L. (1995). The effects of flight deck automation on verbal flight-relevant communication. In R.S. Jensen, & L.A. Rakovan (Eds.), Proceedings of the 8th International Symposium on Aviation Psychology, Columbus, Ohio, April 24-27, 1995, 216-220. Columbus, OH: The Ohio State University.
    Source Type:   Experiment
    Synopsis: In this study, pilots flew one of four different types of aircraft, each having a different levels of automation: B737-200, B737-200-177, B737-300A, and B737-300E. "Pilot activities were recorded throughout 20 three-day trips. [Pilots flew one of four different Boeing aircrafts. The trips averaged 10 departures and arrivals (10 legs of flight) over the three days. For each leg, data were recorded for the period after leaving the gate until leveling off at cruise altitude, and then throughout the descent after leaving cruise altitude until reaching the destination gate. (The cruise portion was not included to keep the length of time in which data were gathered similar across flights.) The activities in which each pilot was engaged were sampled every 7.5 seconds by visual observation, then coded on the data sheet. Up to four codes were recorded at any one time, they included what the pilots were looking at, what they were doing with their hands, whether or not they were speaking, and whether they were performing some global task such as flying the aircraft or communicating with Air Traffic Control. Each activity was coded with one of a possible 65 codes. ... A 4 x 2 x 2 x 4 mixed analysis of variance (ANOVA) was used to analyze effects of automation level, position, duty, and flight segment on the percentage of flight-relevant verbal communication."
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  27.  
  28. Source: Pritchett, A.R. & Johnson, E.N. (1994). Vertical flight path mode awareness experimental study. Paper presented at the Training for Automation Workshop, NASA Ames Research Center, 24-25 Aug 1994.
    Source Type:   Experiment
    Synopsis: "Training for Automation Workshop NASA Ames Research Center August 24-25, 1994" This paper outlines the simulator study conducted to explore incidences occurring in A320 aircraft involving Vertical Speed Mode accidentally being selected instead of Flight Path Angle. The experiment used MIT Advanced Cockpit Simulator in Aeronautical Systems Lab and involved 12 subjects, 7 Captains and 5 First Officers. None of the subjects had had any flight experience in the A320.
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  29.  
  30. Source: Riley, V., Lyall, E., & Wiener, E. (1993). Analytic Methods for Flight-Deck Automation Design and Evaluation, Phase Two Report: Pilot Use of Automation. FAA Contract Number DTFA01-91-C-0039.
    Source Type:   Experiment
    Synopsis: "The purpose of this program was to identify and characterize factors that influence pilot decisions to use or not use automation. Because so little data exist in this area to date, we chose to approach the topic from three directions. First, we used a simple computer-based experiment to gather basic data on how pilot automation use decisions were influenced by changes in workload, task uncertainty, automation reliability, and risk, and how pilot decisions regarding automation use differed from non-pilots. Second, we performed a series of simulator studies in which specific features of the situation were manipulated to determine their effects on automation use decisions. And third, we augmented the simulator study data with a questionnaire in which we asked participating pilots to indicate how factors of interest (workload, self confidence, trust in the automation, urgency, and risk) affect their automation use decisions. Sixty nine commercial transport pilots participated in the computer study and forty in the simulator study. Taken together, these sets of results shed new light on how pilots decide to use or not use automation."
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  31.  
  32. Source: Riley, V.A. (1994). Human use of automation. Unpublished doctoral dissertation, University of Minnesota Department of Psychology.
    Source Type:   Experiment
    Synopsis: "The principal objective of this research is to provide basic empirical evidence on how selected factors influence automation use decisions." Four complementary experiments were performed. "The primary objectives of Experiment One were to investigate the effects of workload, task uncertainty (as a manipulation of self confidence), and automation reliability (as a manipulation of operator trust in the automation) on operator tendencies to use automation." The subjects used in "Experiment One were thirty, University of Minnesota students ... The primary objective of Experiment Three was to compare how professional commercial transport aircraft pilots use automation with how students use it. This comparison is intended to provide insight regarding automation use biases that may result from two levels of experience with automation. ... Thirty four commercial transport pilots from a major airline participated in the study. All pilots were current on an advanced technology aircraft (Boeing 737-300, Boeing 757, or Airbus A320) ... Experiment Three was a replication of Experiment One" and the results of Experiment One were compared to the results of Experiment Three. "Each experiment included a computer-based task, in which subjects had to decide whether or not to rely on automation to perform the task, and a series of questionnaires. ... The computer-based task phase of the experiment consisted of a simple computer game and a gambling task. ... The game phase of the experiment consisted of two tasks which the subject had to perform simultaneously. One of the tasks could be turned over to or taken back from automation at the subject's discretion. The other task required constant attention as a workload manipulation. ... The game phase of the experiment required one hour to perform. There were 2050 trials of 1.75 seconds each. After the game phase, the subject was given an opportunity to gamble for more points. This was intended as an objective measure of risk taking, to be compared with the risk questionnaire results. ... Two questionnaires were used to investigate how individual differences in acceptance of risk and attitudes toward automation might affect automation use. The risk questionnaire used was the Choice Dilemma Questionnaire (Kogan and Wallach, 1964). ... The automation attitudes questionnaire was the Complacency-Potential Rating Scale (Singh and all, 1993)."
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  33.  
  34. Source: Roscoe, A.H. (April, 1992). Workload in the Glass Cockpit. Flight Safety Digest, 1-8.
    Source Type:   Experiment
    Synopsis: This paper describes a Britannia Airways study that began in 1984. "Some of the advantages of new technology were demonstrated in a Britannia Airways study ... it was designed to compare levels of workload experienced during routine passenger flights in the newly introduced Boeing 767 with those experienced in the older Boeing 737-200 - an accepted two-pilot airplane. Workload was assessed by means of a specially designed, 10-point rating scale - the Bedford Scale - augmented by recording the pilot's heart rate. An experienced cockpit observer, seated in the cockpit, recorded details of the flight and also rated the workload using the same scale. During the first phase of the study, 12 pilots were monitored in the 737 and then, after conversion and some experience in type, in the 767."
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  35.  
  36. Source: Sarter, N.B. & Woods, D.D. (1994). Pilot interaction with cockpit automation II: An experimental study of pilot's model and awareness of the Flight Management System. International Journal of Aviation Psychology, 4(1), 1-28. Lawrence Erlbaum Associates.
    Source Type:   Experiment
    Synopsis: "The experimental scenario for this study was designed to address ... issues related to (a) pilots' proficiency in standard tasks, (b) pilots' mental model of the functional structure of the FMS and (c) their awareness of system state and behavior (mode awareness). In cooperation with a flight instructor, we identified tasks and events that would best serve to probe these phenomena. The basic flight context consisted of a flight from Los Angeles to San Francisco which took approximately 60 minutes to complete. ... The participants in this study were 20 airline pilots who responded to postings or who were approached by the airline's training department. Participation was voluntary and pilots were paid a nominal compensation for their cooperation. The participating pilots either had a considerable amount of line experience on the B-737-300 (n=14), or they were about to finish their fixed-base transition training to the B-737-300 (n=6). ... Pilots were asked to fly individually a 60 minute scenario on a fixed-base B-737-300 part-task trainer. This simulator works based on an actual aircraft data base. It is equipped with all relevant cockpit instruments, and it allows for any operation except hand-flying the aircraft below 1,000 ft AGL. Upon arrival at the simulator, pilots were provided with the necessary paperwork (e.g. charts, approach plates, weather, weight manifest) as well as the LAX-ATIS and their clearance ... The participants were asked to take their seat in the cockpit, and to act as Pilot-Flying (PF) during this flight. They were given time to familiarize themselves with the cockpit set-up and the intended flight. The instructor told them that weather was not a consideration, no NOTAMSs existed for the flight, and all appropriate checklists would be completed during the flight. The instructor took care of the cockpit set-up for the participant. He occupied the empty seat and acted as Pilot-Not-Flying (PNF) and ATC throughout the flight. An observer was seated behind both pilots to collect behavioral and verbal data throughout the test run and to introduce scenario events through manipulation of the simulator (e.g., introduction of failures). ... At various points during the scenario, pilots were asked to perform or describe FMS-related tasks, or they were asked questions concerning their FMS-related knowledge. After completion of the flight, additional questions were asked concerning FMS logic and operations, and the pilots were given the chance to ask the instructor about tasks and events that occurred during the test run."
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  37.  
  38. Source: Sarter, N.B. & Woods, D.D. (1995). Strong, Silent, and Out-of-the-loop: Properties of Advanced (Cockpit) Automation and Their Impact on Human-Automation Interaction. CSEL Report 95-TR-01.
    Source Type:   Experiment
    Synopsis: This paper describes " procedures and results of ... research activities that were carried out to examine the nature and circumstances of automation-related problems encountered by A-320 pilots during line operations. ... The final step in the reported line of research was an experimental simulation study of mode awareness and pilot-automation coordination on the flight deck of the A-320. ... Eighteen experienced A-320 pilots were asked to fly a 90-minute scenario on a full-mission A-320 simulator. The scenario for the study was designed to include a variety of tasks and events that represent instantiations of the problems suggested by the survey. ... Behavioral data were collected throughout the flight to infer pilots' level of mode awareness and to examine how they cope with 'automation surprises'. these data were complemented by verbal data gathered during a debriefing to clarify observed behavior."
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  39.  
  40. Source: Skitka, L.J., Mosier, K.L., Burdick, M., & Rosenblatt, B. (2000). Automation bias and errors: Are crews better than individuals?. International Journal of Aviation Psychology, 10(1), 85-97. Lawrence Erlbaum Associates.
    Source Type:   Experiment
    Synopsis: "The availability of automated decision aids can sometimes feed into the general human tendency to travel the road of least cognitive effort. Is this tendency toward “automation bias” (the use of automation as a heuristic replacement for vigilant information seeking and processing) ameliorated when more than one decision maker is monitoring system events? This study examined automation bias in two-person crews versus solo performers under varying instruction conditions. Training that focused on automation bias and associated errors successfully reduced commission, but not omission, errors. Teams and solo performers were equally likely to fail to respond to system irregularities or events when automated devices failed to indicate them, and to incorrectly follow automated directives when they contradicted other system information."
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  41.  
  42. Source: Speyer, J.J. & Blomberg, R.D. (1989). Workload and automation. In Proceedings of the 2nd Conference of Human Error Avoidance Techniques, Herndon, VA, September 18-19, 1989.
    Source Type:   Experiment
    Synopsis: "While one of the design goals of automation is to reduce crew workload, little is known about the true relationship between workload and automation. This paper discusses the approaches taken by Airbus Industrie when designing increasing levels of automation into their aircraft. ... The Airbus approach to workload measurement and estimation assumes that the pilot himself can best judge workload by integrating the various workload dimensions into a single scale rating. ... It involves interrogating the pilots for scaled workload assessment ratings throughout the minimum crew certification route-proving flights." The information gathered from the A310 certification was then used to develop the Airbus Workload Model which is "a mathematical model of the rating process. ... Workload measures calculated by the Model were used to demonstrate the workload characteristics of the A320 as partial fulfillment of the requirements for its certification." Data was "collected during the minimum crew certification flights for the A320."
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  43.  
  44. Source: Speyer, J.J., Blomberg, R.D., & Fouillot, J.P. (1990). Evaluation the Impact of New Technology Cockpits: Onwards from A300FF, A310, A320 to A330, A340. In Proceedings of the International Conference on Human Machine Interaction and Artificial Intelligence in Aeronautics and Space.
    Source Type:   Experiment
    Synopsis: Airbus Industrie conceived a comparative test between the sidestick/fly-by-wire combination and conventional controls. "... the conventional controls for the CM1 (left) were removed and replaced with a sidestick. ...A 'base training' circuit was designed to pose a variety of flying problems for two engineering test pilots neither of whom had flown fly-by-wire before. Three different operational conditions were experimented, i.e. flight director (with autothrottle), ILS (raw data without autothrottle), NDB."
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  45.  
  46. Source: Speyer, J.J., Fort, A., Fouillot, J.P., & Blomberg, R.D. (1987). Assessing pilot workload for minimum crew certification. The Practical Assessment of Pilot Workload, 90-115. AGARDograph No. 282. London: North Atlantic Treaty Organization Advisory Group for Aerospace Research and Development.
    Source Type:   Experiment
    Synopsis: "The static taskload method allows an objective quantitative task analysis of system management procedures that attempts to quantify the ergonomic aspects (visibility, observability, accessibility, operability, monitorability of control and displays) of the man-machine interface of a new aircraft through a direct comparison of procedures with a previously certificated two-person aircraft. It provides quantitative taskload data or in other words objective indications of individual crewmember task demand by measuring the impact of a new cockpit layout, the location and nature of controls and indicators in comparison with a former cockpit layout. After selecting a series of comparable normal, abnormal and emergency procedures each of these procedures is analysed individually for both aircraft. Each task in a given procedure is split into 6 basic actions i.e. look, observe, monitor, reach, operate and monitor (the result of the operation) ... Each action is linked with a feasibility index which expresses the elementary difficulty to accomplish this action. These visibility, observability, accessibility, operability, monitorability indices are intimately linked with the cockpit layout or hardware. They are expressed in terms of values on a continuous difficulty scale ranging from 0 to 1, the static taskload scale... [This paper discusses] the A300FF minimum crew certification [in which] the Static Taskload Analysis was comparatively applied to the A300FF and the MCDONNELL DOUGLAS DC-9. ... Comparable normal, abnormal and emergency procedures were selected ... This involved at least 10 normal procedures and 10 abnormal/emergency procedures. ... Task analyses of system management activities were performed for each crew member of each aircraft with a task breakdown into basic actions (look, observe, monitor, reach, operate and monitor) CM1 (or the left hand seated pilot) being PF, CM2 acting as PNF; the task analyses of the A300FF ... [was] conducted in [a mockup]; .... the task analyses of the ... [DC-9 was] conducted in a flight simulator with the assistance of a type rated flight instructor. ... Geometric, time and mechanical measurements from cockpit drawings, mock-up and simulators were used to calculate parameters that are considered in mathematical models of ergonomic feasibility laws. ... Feasibility indices for each action of a task are calculated by means of the mathematical models of each type of action. ... Taskload matrices were compiled for each procedure so that comparisons could be made between the aircraft under evaluation and the reference aircraft, initial results for each crewmember (CM1 or CM2) and for each procedure are expressed in terms of Burden and Weighed Average Taskload; Burden gives a measurement of the overall amount of work demanded for executing a particular procedure, whereas Weighted Average Taskload gives as idea of the average degree of difficulty generated y the execution of a procedure. ... Histogrammic plots of Burden and weighted average taskload for each crewmember were drawn allowing to take first hand conclusions."
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  47.  
  48. Source: Speyer, J.J., Monteil, C., Blomberg, R.D., & Fouillot, J.P. (1990). Impact of New Technology on Operational Interface: From Design Aims to Flight Evaluation and Measurement. Advisory Group for Aerospace Research and Development No. 301, Vol. 1.
    Source Type:   Experiment
    Synopsis: "Two experimental studies were performed in cooperation with DUNLAP & ASSOCIATIES (Hartford, Connecticut, USA) to investigate the impact of new digital equipment that was to be installed in the A310. ... studies were undertaken to compare the overall performance of the pilot/aircraft system between flights using conventional, electromechanical primary flight instruments and those flown with the new, electronic flight instruments (EFIS) and the flight management system (FMS). Data collection for the EFIS experiment was undertaken in an A300 flight test & development aircraft (MSN 003) which for this purpose was specifically equipped with conventional instruments installed in front of the left seat position and EFIS installed in the right seat position. Data collection for the FMS experiment was undertaken in production A310 which had both the EFIS and FMS at both pilot positions. ... both studies utilized a design in which relevant parameters were systematically varied as the experimental subjects (senior Airbus test pilots who had never flown with EFIS nor FMS before) repeatedly flew specifically designed circuits."
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