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At least 163 records · Page 9

Entropy, instrument scan and pilot workload

Correlation and information theory which analyze the relationships between mental loading and visual scanpath of aircraft pilots are described. The relationship between skill, performance, mental workload, and visual scanning behavior are investigated. The experimental method required pilots to maintain a general aviation flight simulator on a straight and level, constant sensitivity, Instrument Landing System (ILS) course with a low level of turbulence. An additional periodic verbal task whose difficulty increased with frequency was used to increment the subject's mental workload. The subject's looppoint on the instrument panel during each ten minute run was computed via a TV oculometer and stored. Several pilots ranging in skill from novices to test pilots took part in the experiment. Analysis of the periodicity of the subject's instrument scan was accomplished by means of correlation techniques. For skilled pilots, the autocorrelation of instrument/dwell times sequences showed the same periodicity as the verbal task. The ability to multiplex simultaneous tasks increases with skill. Thus autocorrelation provides a way of evaluating the operator's skill level.

Tole, J. R.↗

TPSAS-NF1676L-11455-DND

Adaptive control is well suited for rapidly changing, highly uncertain, and potentially unpredictable, flight dynamics characteristic of upset or damage induced on transport as well as high-performance aircraft. Some of the recent flight experiences of pilot-in-the-loop with an adaptive controller have exhibited unpredicted interactions. In retrospect, this is not surprising once it is realized that there are now two adaptive controllers interacting, the traditional software adaptive control system and the pilot. In order to capture the interaction between the adaptive controller and the pilot, research is being conducted to characterize the pilot as an adaptive controller, to define the interaction between pilots and adaptive controllers, and to then specify the behavior of the controller and the function allocation between the pilot and the adaptive controller during adaptation. This presentation will explain the methodology employed in the current research involving the use of system identification techniques to help characterize pilots and to characterize the interaction of an adaptive controller with a pilot. In particular, system identification appears to be a viable technique for modeling a pilot. Also touched upon in this presentation are possible avenues of augmenting the Hess simplified pursuit model and planned research to further characterize a pilot’s interaction with an adaptive controller.

Anna Trujillo↗

Pre-Study Walkthrough with a Commercial Pilot for a Preliminary Single Pilot Operations Experiment

The number of crew members in commercial flights has decreased to two members, down from the five-member crew required 50 years ago. One question of interest is whether the crew should be reduced to one pilot. In order to determine the critical factors involved in safely transitioning to a single pilot, research must examine whether any performance deficits arise with the loss of a crew member. With a concrete understanding of the cognitive and behavioral role of a co-pilot, aeronautical technologies and procedures can be developed that make up for the removal of the second aircrew member. The current project describes a pre-study walkthrough process that can be used to help in the development of scenarios for testing future concepts and technologies for single pilot operations. Qualitative information regarding the tasks performed by the pilots can be extracted with this technique and adapted for future investigations of single pilot operations.

Single Pilot Operations↗

Team play with a powerful and independent agent: operational experiences and automation surprises on the Airbus A-320

Research and operational experience have shown that one of the major problems with pilot-automation interaction is a lack of mode awareness (i.e., the current and future status and behavior of the automation). As a result, pilots sometimes experience so-called automation surprises when the automation takes an unexpected action or fails to behave as anticipated. A lack of mode awareness and automation surprises can he viewed as symptoms of a mismatch between human and machine properties and capabilities. Changes in automation design can therefore he expected to affect the likelihood and nature of problems encountered by pilots. Previous studies have focused exclusively on early generation "glass cockpit" aircraft that were designed based on a similar automation philosophy. To find out whether similar difficulties with maintaining mode awareness are encountered on more advanced aircraft, a corpus of automation surprises was gathered from pilots of the Airbus A-320, an aircraft characterized by high levels of autonomy, authority, and complexity. To understand the underlying reasons for reported breakdowns in human-automation coordination, we also asked pilots about their monitoring strategies and their experiences with and attitude toward the unique design of flight controls on this aircraft.

NASA Discipline Space Human Factors↗

Combustor-Turbine Interactions By Using the Open National Combustion Code (OpenNCC) and the Glenn-HT Code

We develop the methodology of coupling two different computational fluid dynamic (CFD) codes, OpenNCC and Glenn-HT, in order to investigate the unsteady flow fields inside the combustor and around the first-stage stator of a high-pressure turbine (HPT) from the energy efficient engine (E 3 ) program. In our coupling strategy, OpenNCC, a time accurate unstructured mesh multi-phase combustion CFD code, is applied to the combustor region and Glenn-HT, a structured mesh CFD code designed for turbine applications, is utilized inside the HPT region. As a proof of concept, we first simulate the three-dimensional airflow over the backward facing step and compared the predicted pressure coefficient against experimental data. We then considered a Jet-A/Air combustor with the NASA single learn direct injector (LDI) as a reacting flow test case. Here, Glenn-HT is used in the downstream of the combustor and assumes that the working fluid is a single gas (i.e., air) where the properties of the gas are taken from time- and area-averaged values at the combustor exit. A fully coupled combustor-turbine simulation using both OpenNCC and Glenn-HT was conducted on the E 3 combustor and a detailed analysis done pertaining to how a realistic combustor outflow affects migration of hot-streaks and its impact on the aerodynamic behavior inside the HPT. It is found that the combustion dynamics (i.e., the switching main and pilot flame strength) significantly alters the aerodynamic behavior inside the HPT including hot-streak migration. Variations of the temperature and the velocity magnitude in the passage could be up to ±75 and ±15. These large variations are an important part of the combustor-turbine interactions, which are overlooked by a single component simulation of the HPT while imposing the steady inflow boundary condition at the HPT inlet. Finally, it is observed the strong density gradient associated with the hot-streaks and the pressure gradient at the passage significantly enhances the baroclinic torque, affecting the vorticity field.

CFD hot-streaks↗

Towards Validation of an Adaptive Flight Control Simulation Using Statistical Emulation

Traditional validation of flight control systems is based primarily upon empirical testing. Empirical testing is sufficient for simple systems in which a.) the behavior is approximately linear and b.) humans are in-the-loop and responsible for off-nominal flight regimes. A different possible concept of operation is to use adaptive flight control systems with online learning neural networks (OLNNs) in combination with a human pilot for off-nominal flight behavior (such as when a plane has been damaged). Validating these systems is difficult because the controller is changing during the flight in a nonlinear way, and because the pilot and the control system have the potential to co-adapt in adverse ways traditional empirical methods are unlikely to provide any guarantees in this case. Additionally, the time it takes to find unsafe regions within the flight envelope using empirical testing means that the time between adaptive controller design iterations is large. This paper describes a new concept for validating adaptive control systems using methods based on Bayesian statistics. This validation framework allows the analyst to build nonlinear models with modal behavior, and to have an uncertainty estimate for the difference between the behaviors of the model and system under test.

He, Yuning↗

CDTI: Crew Function Assessment

Man machine interaction often requires the operator to perform a sterotyped scan of instruments to monitor and/or control a system. Situations in which this type of behavior exists, such as instrument flight, scan pattern has been shown to be altered by imposition of simultaneous verbal tasks. The relationship between pilot visual scan of instruments and mental workload was described. A verbal loading task of varying difficulty caused pilots to stare at the primary instrument as the difficulty increased and to shed looks at instruments of less importance. The verbal loading task affected rank ordering of scanning sequences. The behavior of pilots with widely varying skill levels suggested that these effects occur most strongly at lower skill levels and are less apparent at high skill levels. Graphical interpretation of the hypothetical relationship between skill, workload, and performance is introduced and modeling results are presented to support this interpretation.

Tole, J. R.↗

Simulator model specification for the augmentor wing jet STOL research aircraft

The configuration and simulation studies of a C-8A (De Havilland Buffalo) aircraft are described. The modifications to STOL configuration consisted of augmentor-wing jet flaps, blown and drooped ailerons, and leading edge slats. The total simulator model includes a number of component parts for producing realistic visual, aural, tactile, vestibular, and kinesthetic cues for the pilot to assess the predicted behavior of the real airplane.

Rumsey, P. C.↗

A human operator simulator model of the NASA Terminal Configured Vehicle (TCV)

A generic operator model called HOS was used to simulate the behavior and performance of a pilot flying a transport airplane during instrument approach and landing operations in order to demonstrate the applicability of the model to problems associated with interfacing a crew with a flight system. The model which was installed and operated on NASA Langley's central computing system is described. Preliminary results of its application to an investigation of an innovative display system under development in Langley's terminal configured vehicle program are considered.

Glenn, F. A., III↗

In-flight assessment of workload using instrument scan

During instrument flight, the pilot obtains information concerning aircraft state by cross checking or scanning the flight instruments. The exact method of scanning the instrument panel varies from pilot to pilot but there are some basic features common to a good scan pattern. The method discussed may be considered a candidate for workload studies with piloting tasks which will invoke a regular visual scan (spatial/temporal pattern of eye movements) during instrument flight. It is important to point out that instrument scan by itself is not a complete indicator of workload nor is task attention necessarily associated with where the pilot happens to be looking at a particular instant. However, whenever instrument scan is required in a piloting task, analysis of scanning behavior may yield important direct or indirect information concerning workload.

Tole, J. R.↗

Neural Flight Control System

The Neural Flight Control System (NFCS) was developed to address the need for control systems that can be produced and tested at lower cost, easily adapted to prototype vehicles and for flight systems that can accommodate damaged control surfaces or changes to aircraft stability and control characteristics resulting from failures or accidents. NFCS utilizes on a neural network-based flight control algorithm which automatically compensates for a broad spectrum of unanticipated damage or failures of an aircraft in flight. Pilot stick and rudder pedal inputs are fed into a reference model which produces pitch, roll and yaw rate commands. The reference model frequencies and gains can be set to provide handling quality characteristics suitable for the aircraft of interest. The rate commands are used in conjunction with estimates of the aircraft s stability and control (S&C) derivatives by a simplified Dynamic Inverse controller to produce virtual elevator, aileron and rudder commands. These virtual surface deflection commands are optimally distributed across the aircraft s available control surfaces using linear programming theory. Sensor data is compared with the reference model rate commands to produce an error signal. A Proportional/Integral (PI) error controller "winds up" on the error signal and adds an augmented command to the reference model output with the effect of zeroing the error signal. In order to provide more consistent handling qualities for the pilot, neural networks learn the behavior of the error controller and add in the augmented command before the integrator winds up. In the case of damage sufficient to affect the handling qualities of the aircraft, an Adaptive Critic is utilized to reduce the reference model frequencies and gains to stay within a flyable envelope of the aircraft.

Gundy-Burlet, Karen↗

Analyses of the Boeing 737-MAX Accidents: Formal Models and Psychological Perspectives

Two fatal accidents involving the B737MAX resulted from the flight crews’ inability to overcome the effects of the Maneuvering Characteristics Augmentation System (MCAS). MCAS was designed to mimic the control column feel pressure and pitching behavior of the B737NG, which was the certification basis for the B737MAX. We briefly describe the potential role of formally modeling different perspectives during system design, and how such modeling can reveal gaps and conflicts between perspectives. We also discuss some of the relevant human factors issues involved in these accidents and how the aircraft’s behavior may have affected the pilots’ psychological states. Implications for automation design are considered.

5737MAX↗

Pilot Non-Conformance to Alerting System Commands

Instances of pilot non-conformance to alerting system commands have been identified in previous studies. Pilot non-conformance changes the final behavior of the system, and therefore may reduce actual performance from that anticipated. A simulator study has examined pilot non-conformance, using the task of collision avoidance during closely spaced parallel approaches as a case study. Consonance between the display and the alerting system was found to significantly improve subject agreement with automatic alerts. Based on these results, a more general discussion of the factors involved in pilot conformance is given, and design guidelines for alerting systems are given.

Pritchett, Amy R.↗

Autogenic Feedback Training Exercise and pilot performance: enhanced functioning under search-and-rescue flying conditions

Studies have shown that autonomous mode behavior is one cause of aircraft fatalities due to pilot error. In such cases, the pilot is in a high state of psychological and physiological arousal and tends to focus on one problem, while ignoring more critical information. This study examined the effect of training in physiological self-recognition and regulation, as a means of improving crew cockpit performance. Seventeen pilots were assigned to the treatment and control groups matched for accumulated flight hours. The treatment group contained 4 pilots from HC-130 Hercules aircraft and 4 HH-65 Dolphin helicopter pilots; the control group contained 3 pilots of HC-130s and 6 helicopter pilots. During an initial flight, physiological data were recorded on each crewmember and an instructor pilot rated individual crew performance. Eight crewmembers were then taught to regulate their own physiological response levels using Autogenic-Feedback Training Exercise (AFTE). The remaining participants received no training. During a second flight, treatment participants showed significant improvement in performance (rated by the same instructor pilot as in pretests) while controls did not improve. The results indicate that AFTE management of high states of physiological arousal may improve pilot performance during emergency flying conditions.

NASA Discipline Neuroscience↗

The effectiveness of incorporating a real-time oculometer system in a commercial flight training program

The effectiveness of incroporating a real-time oculometer system into a Boeing 737 commercial flight training program was studied. The study combined a specialized oculometer system with sophisticated video equipment that would allow instructor pilots (IPs) to monitor pilot and copilot trainees' instrument scan behavior in real-time, and provide each trainee with video tapes of his/her instrument scanning behavior for each training session. The IPs' performance ratings and trainees' self-ratings were compared to the performance ratings by IPs and trainees in a control group. The results indicate no difference in IP ratings or trainees' self-ratings for the control and experimental groups. The results indicated that the major beneficial role of a real-time oculometer system for pilots and copilots having a significant amount of flight experience would be for problem solving or refinement of instrument scanning behavior rather than a general instructional scheme. It is suggested that this line of research be continued with the incorporation of objective data (e.g., state of the aircraft data), measures of cost effectiveness and with trainees having less flight experience.

Jones, D. H.↗

Modelling decision-making by pilots

Our scientific goal is to understand the process of human decision-making. Specifically, a model of human decision-making in piloting modern commercial aircraft which prescribes optimal behavior, and against which we can measure human sub-optimality is sought. This model should help us understand such diverse aspects of piloting as strategic decision-making, and the implicit decisions involved in attention allocation. Our engineering goal is to provide design specifications for (1) better computer-based decision-aids, and (2) better training programs for the human pilot (or human decision-maker, DM).

Patrick, Nicholas J. M.↗

Formal Aspects of Human-Automation Interaction

While new versions of automated control systems such as flight guidance systems are introduced at a rapid pace, it is widely recognized that user interaction with these machines is increasingly problematic. One cause for this difficulty that is commonly cited in the literature, is the discrepancy between the machine's behavior and the operator's (e.g., pilot) expectations. This paper discusses a formal approach to the analysis of operator's interaction with complex automated control systems. We focus attention on the issue of interface correctness; that is, on the question whether the display provides adequate information about the machine's configurations (states, modes, and associated parameters) and transitions, so as to enable the operator to successfully perform the specified set of tasks. To perform the analysis several assumptions are made: (1) A complete formal model of the machine's behavior is available (e.g., as a state transition system, or as a hybrid-machine); (2) A specification of operator's tasks is available and can be formally described (e.g., the reliable and predictable transition between activities involved in executing a climb to a new altitude); (3) The pilot is well trained and has a correct 'mental' model of the machine's response-map. By 'comparing' the machine's model with the set of operator's tasks we formally (i.e., mathematically) evaluate two questions: 1) does the machine's output interface (display) enable the operator to determine, unambiguously, what the current configuration (e.g., mode) of the machine is, and 2) does the display enable the operator to determine, unambiguously, what the next configuration of the machine will be, in response to a specified interaction by the operator (e.g., engaging a mode or changing a parameter such as a speed or target altitude). This paper describes a methodology for conducting such an evaluation using examples from automated flight control systems of modem 'glass cockpit' jetliners. Taxonomy of the different types of discrepancies that lead to pilot inability to resolve the current and next configuration of the machine is suggested. Data from incident reports involving 'mode confusion' is used to corroborate these discrepancies. Finally, means for compensating, either by augmenting the display and/or the operator's 'mental model' are briefly mentioned.

Degani, Asaf↗

Pilot interaction with cockpit automation 2: An experimental study of pilots' model and awareness of the Flight Management System

Technological developments have made it possible to automate more and more functions on the commercial aviation flight deck and in other dynamic high-consequence domains. This increase in the degrees of freedom in design has shifted questions away from narrow technological feasibility. Many concerned groups, from designers and operators to regulators and researchers, have begun to ask questions about how we should use the possibilities afforded by technology skillfully to support and expand human performance. In this article, we report on an experimental study that addressed these questions by examining pilot interaction with the current generation of flight deck automation. Previous results on pilot-automation interaction derived from pilot surveys, incident reports, and training observations have produced a corpus of features and contexts in which human-machine coordination is likely to break down (e.g., automation surprises). We used these data to design a simulated flight scenario that contained a variety of probes designed to reveal pilots' mental model of one major component of flight deck automation: the Flight Management System (FMS). The events within the scenario were also designed to probe pilots' ability to apply their knowledge and understanding in specific flight contexts and to examine their ability to track the status and behavior of the automated system (mode awareness). Although pilots were able to 'make the system work' in standard situations, the results reveal a variety of latent problems in pilot-FMS interaction that can affect pilot performance in nonnormal time critical situations.

Sarter, Nadine B.↗