Automation bias: decision making and performance in high-tech cockpits

Automated aids and decision support tools are rapidly becoming indispensable tools in high-technology cockpits and are assuming increasing control of"cognitive" flight tasks, such as calculating fuel-efficient routes, navigating, or detecting and diagnosing system malfunctions and abnormalities. 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 lilkely to erroneously "remember" the presence of expected cues when describing their decision-making processes.

Effects of adaptive task allocation on monitoring of automated systems

The effects of adaptive task allocation on monitoring for automation failure during multitask flight simulation were examined. Participants monitored an automated engine status task while simultaneously performing tracking and fuel management tasks over three 30-min sessions. Two methods of adaptive task allocation, both involving temporary return of the automated engine status task to the human operator ("human control"), were examined as a possible countermeasure to monitoring inefficiency. For the model-based adaptive group, the engine status task was allocated to all participants in the middle of the second session for 10 min, following which it was again returned to automation control. The same occurred for the performance-based adaptive group, but only if an individual participant's monitoring performance up to that point did not meet a specified criterion. For the nonadaptive control groups, the engine status task remained automated throughout the experiment. All groups had low probabilities of detection of automation failures for the first 40 min spent with automation. However, following the 10-min intervening period of human control, both adaptive groups detected significantly more automation failures during the subsequent blocks under automation control. The results show that adaptive task allocation can enhance monitoring of automated systems. Both model-based and performance-based allocation improved monitoring of automation. Implications for the design of automated systems are discussed.

A closed-loop system for examining psychophysiological measures for adaptive task allocation

A closed-loop system was evaluated for its efficacy in using psychophysiological indexes to moderate workload. Participants were asked to perform either 1 or 3 tasks from the Multiattribute Task Battery and complete the NASA Task Load Index after each trial. An electroencephalogram (EEG) was sampled continuously while they performed the tasks, and an EEG index (beta/alpha plus theta) was derived. The system made allocation decisions as a function of the level of operator engagement based on the value of the EEG index. The results of the study demonstrated that it was possible to moderate an operator's level of engagement through a closed-loop system driven by the operator's own EEG. In addition, the system had a significant impact on behavioral, subjective, and psychophysiological correlates of workload as task load increased. The theoretical and practical implications of these results for adaptive automation are discussed.

Can Unmanned Aerial Systems (Drones) Be Used for the Routine Transport of Chemistry, Hematology, and Coagulation Laboratory Specimens?

BACKGROUND

Unmanned Aerial Systems (UAS or drones) could potentially be used for the routine transport of small goods such as diagnostic clinical laboratory specimens. To the best of our knowledge, there is no published study of the impact of UAS transportation on laboratory tests.

METHODS

Three paired samples were obtained from each one of 56 adult volunteers in a single phlebotomy event (336 samples total): two tubes each for chemistry, hematology, and coagulation testing respectively. 168 samples were driven to the flight field and held stationary. The other 168 samples were flown in the UAS for a range of times, from 6 to 38 minutes. After the flight, 33 of the most common chemistry, hematology, and coagulation tests were performed. Statistical methods as well as performance criteria from four distinct clinical, academic, and regulatory bodies were used to evaluate the results.

RESULTS

Results from flown and stationary sample pairs were similar for all 33 analytes. Bias and intercepts were <10% and <13% respectively for all analytes. Bland-Altman comparisons showed a mean difference of 3.2% for Glucose and <1% for other analytes. Only bicarbonate did not meet the strictest (Royal College of Pathologists of Australasia Quality Assurance Program) performance criteria. This was due to poor precision rather than bias. There were no systematic differences between laboratory-derived (analytic) CV's and the CV's of our flown versus terrestrial sample pairs however CV's from the sample pairs tended to be slightly higher than analytic CV's. The overall concordance, based on clinical stratification (normal versus abnormal), was 97%. Length of flight had no impact on the results.

CONCLUSIONS

Transportation of laboratory specimens via small UASs does not affect the accuracy of routine chemistry, hematology, and coagulation tests results from selfsame samples. However it results in slightly poorer precision for some analytes.

Head-up displays: effects of clutter, display intensity, and display location on pilot performance

Two experiments examined the effects of display location (head-up and head-down), display clutter, and display intensity on pilot performance in a general aviation-cruise flight environment. In Experiment 1, a low-fidelity simulation revealed that the detection of commanded flight changes and flight-path tracking performance was better in the head-down condition as compared to the head-up condition. In contrast, midair traffic detection was superior with the head-up display (HUD), reflecting an attentional trade-off. Experiment 2 used the same paradigm in a high-fidelity visual simulation. Flight performance was equivalent between HUD and head-down locations. Detection of commanded changes and traffic was better in the HUD condition, revealing the HUD benefits of reduced scanning. The presence of clutter inhibited detection of command changes and traffic in both head-up and head-down conditions. Lowlighting the task-irrelevant clutter did not facilitate detection of commanded changes, however, the clutter cost for detecting traffic was diminished if the added information was lowlighted in the head-down location. The data suggested that attention was modulated between tasks (flight control and detection), and between display areas (head-up and head-down).

Electronic maps for terminal area navigation: effects of frame of reference and dimensionality

Two experiments are reported that contrast rotating versus fixed electronic map displays, which pilots used for a simulated approach to a landing. In Experiment 1, a rotating versus fixed-map display was experimentally crossed with a two-dimensional (2D) versus three-dimensional (3D) view (perspective map) as pilots' ability to maintain the flight path and demonstrate awareness of the location of surrounding terrain features were assessed. Rotating displays supported better flight path guidance and did not substantially harm performance on terrain awareness tasks. 3D displays led to a substantial cost for vertical control but did not differ from 2D displays in lateral control. In Experiment 2, pilots flew with the rotating 2D display and with an improved version of the rotating 3D display, designed to reduce the ambiguity of representing altitude information. Vertical control improved as a result of the 3D display design improvement, but lateral control did not. The results are discussed in terms of the costs and benefits of presenting information in 3D, ego-referenced format for both flight path control and terrain awareness.

Drones in medicine-The rise of the machines

This is a medical kitty hawk moment. Drones are pilotless aircrafts that were initially used exclusively by the military but are now also used for various scientific purposes, public safety, and in commercial industries. The healthcare industry in particular can benefit from their technical capabilities and ease of use. Common drone applications in medicine include the provision disaster assessments when other means of access are severely restricted; delivering aid packages, medicines, vaccines, blood and other medical supplies to remote areas; providing safe transport of disease test samples and test kits in areas with high contagion; and potential for providing rapid access to automated external defibrillators for patients in cardiac arrest. Drones are also showing early potential to benefit geriatric medicine by providing mobility assistance to elderly populations using robot-like technology. Looking further to the future, drones with diagnostic imaging capabilities may have a role in assessing health in remote communities using telemedicine technology. The Federal Aviation Administration (FAA) in the United States and the European Aviation Safety Agency (EASA) in the European Union are some examples of legislative bodies with regulatory authority over drone usage. These agencies oversee all technical, safety, security and administrative issues related to drones. It is important that drones continue to meet or exceed the requirements specified in each of these regulatory areas. The FAA is challenged with keeping pace legislatively with the rapid advances in drone technology. This relative lag has been perceived as slowing the proliferation of drone use. Despite these regulatory limitations, drones are showing significant potential for transforming healthcare and medicine in the 21st century.

Supporting trust calibration and the effective use of decision aids by presenting dynamic system confidence information

OBJECTIVE

To examine whether continually updated information about a system's confidence in its ability to perform assigned tasks improves operators' trust calibration in, and use of, an automated decision support system (DSS).

BACKGROUND

The introduction of decision aids often leads to performance breakdowns that are related to automation bias and trust miscalibration. This can be explained, in part, by the fact that operators are informed about overall system reliability only, which makes it impossible for them to decide on a case-by-case basis whether to follow the system's advice.

METHOD

The application for this research was a neural net-based decision aid that assists pilots with detecting and handling in-flight icing encounters. A multifactorial experiment was carried out with two groups of 15 instructor pilots each flying a series of 28 approaches in a motion-base simulator. One group was informed about the system's overall reliability only, whereas the other group received updated system confidence information.

RESULTS

Pilots in the updated group experienced significantly fewer icing-related stalls and were more likely to reverse their initial response to an icing condition when it did not produce desired results. Their estimate of the system's accuracy was more accurate than that of the fixed group.

CONCLUSION

The presentation of continually updated system confidence information can improve trust calibration and thus lead to better performance of the human-machine team.

APPLICATION

The findings from this research can inform the design of decision support systems in a variety of event-driven high-tempo domains.

The potential use of unmanned aircraft systems (drones) in mountain search and rescue operations

OBJECTIVE

This study explores the potential use of drones in searching for and locating victims and of motorized transportation of search and rescue providers in a mountain environment using a simulation model.

METHODS

This prospective randomized simulation study was performed in order to compare two different search and rescue techniques in searching for an unconscious victim on snow-covered ground. In the control arm, the Classical Line Search Technique (CLT) was used, in which the search is performed on foot and the victim is reached on foot. In the intervention arm, the Drone-snowmobile Technique (DST) was used, the search being performed by drone and the victim reached by snowmobile. The primary outcome of the study was the comparison of the two search and rescue techniques in terms of first human contact time.

RESULTS

Twenty search and rescue operations were conducted in this study. Median time to arrival at the mannequin was 57.3min for CLT, compared to 8.9min for DST. The median value of the total searched area was 88,322.0m² for CLT and 228,613.0m² for DST. The median area searched per minute was 1489.6m² for CLT and 32,979.9m² for DST (p<0.01 for all comparisons).

CONCLUSIONS

In conclusion, a wider area can be searched faster by drone using DST compared to the classical technique, and the victim can be located faster and reached earlier with rescuers transported by snowmobile.

Dual-frequency piezoelectric transducers for contrast enhanced ultrasound imaging

For many years, ultrasound has provided clinicians with an affordable and effective imaging tool for applications ranging from cardiology to obstetrics. Development of microbubble contrast agents over the past several decades has enabled ultrasound to distinguish between blood flow and surrounding tissue. Current clinical practices using microbubble contrast agents rely heavily on user training to evaluate degree of localized perfusion. Advances in separating the signals produced from contrast agents versus surrounding tissue backscatter provide unique opportunities for specialized sensors designed to image microbubbles with higher signal to noise and resolution than previously possible. In this review article, we describe the background principles and recent developments of ultrasound transducer technology for receiving signals produced by contrast agents while rejecting signals arising from soft tissue. This approach relies on transmitting at a low-frequency and receiving microbubble harmonic signals at frequencies many times higher than the transmitted frequency. Design and fabrication of dual-frequency transducers and the extension of recent developments in transducer technology for dual-frequency harmonic imaging are discussed.

Information complexity--mental workload and performance in combat aircraft

The purpose of the present study was to analyse the effects of information complexity on Pilot Mental WorkLoad (PMWL) and Pilot Performance (PP), and to analyse the structure of PMWL. Eighteen pilots performed 72 simulated low level-high speed emissions. The complexity of the Head Down Display (HDD) information varied as a function of the tactical situation. Flight data were recorded continuously. The pilots' eye movements were video taped and psychophysiological activation data, Heart Rate (HR), were obtained. The pilots rated PMWL according to the psychological content of three scales (Bedford Rating Scale, Subjective Workload Assessment Technique, NASA-Task Load indeX) and answered a questionnaire tapping aspects of performance, information load, motivation and mood. It was found that even a moderate complexity of information interfered with the flight task. Altitude and variation in altitude were increased and corrections of altitude errors were delayed, when complexity increased. Changes in information load reached its maximum influence on flight performance (r = 0.60, p < 0.001) after a time delay of 20 to 40 seconds. Performance of the flight task correlated positively (r = 0.59, p <0.001) with the performance of the information handling task (Tactical Situation Awareness, TSA). Durations and frequencies of eye fixations Head Up (HU) versus Head Down (HD) changed as a function of information load. A structural equation model implied that PMWL was affected by mission complexity and that PMWL affected objective and subjective aspects of flight performance and information handling. Heart rate (sortie means) correlated positively with PMWL (r = 0.34, p <0.05) and perceived complexity of mission (r = 0.37, p < 0.01). Heart rate (running means) covaried with variations in information complexity for those pilots who performed well. From spectral analyses of cardiac interval times it was found that the amplitude of the 0.10 Hz component tended to decrease during high as compared to low levels of information load.

Designing for flexible interaction between humans and automation: delegation interfaces for supervisory control

OBJECTIVE

To develop a method enabling human-like, flexible supervisory control via delegation to automation.

BACKGROUND

Real-time supervisory relationships with automation are rarely as flexible as human task delegation to other humans. Flexibility in human-adaptable automation can provide important benefits, including improved situation awareness, more accurate automation usage, more balanced mental workload, increased user acceptance, and improved overall performance.

METHOD

We review problems with static and adaptive (as opposed to "adaptable") automation; contrast these approaches with human-human task delegation, which can mitigate many of the problems; and revise the concept of a "level of automation" as a pattern of task-based roles and authorizations. We argue that delegation requires a shared hierarchical task model between supervisor and subordinates, used to delegate tasks at various levels, and offer instruction on performing them. A prototype implementation called Playbook is described.

RESULTS

On the basis of these analyses, we propose methods for supporting human-machine delegation interactions that parallel human-human delegation in important respects. We develop an architecture for machine-based delegation systems based on the metaphor of a sports team's "playbook." Finally, we describe a prototype implementation of this architecture, with an accompanying user interface and usage scenario, for mission planning for uninhabited air vehicles.

CONCLUSION

Delegation offers a viable method for flexible, multilevel human-automation interaction to enhance system performance while maintaining user workload at a manageable level.

APPLICATION

Most applications of adaptive automation (aviation, air traffic control, robotics, process control, etc.) are potential avenues for the adaptable, delegation approach we advocate. We present an extended example for uninhabited air vehicle mission planning.

Flocking algorithm for autonomous flying robots

Animal swarms displaying a variety of typical flocking patterns would not exist without the underlying safe, optimal and stable dynamics of the individuals. The emergence of these universal patterns can be efficiently reconstructed with agent-based models. If we want to reproduce these patterns with artificial systems, such as autonomous aerial robots, agent-based models can also be used in their control algorithms. However, finding the proper algorithms and thus understanding the essential characteristics of the emergent collective behaviour requires thorough and realistic modeling of the robot and also the environment. In this paper, we first present an abstract mathematical model of an autonomous flying robot. The model takes into account several realistic features, such as time delay and locality of communication, inaccuracy of the on-board sensors and inertial effects. We present two decentralized control algorithms. One is based on a simple self-propelled flocking model of animal collective motion, the other is a collective target tracking algorithm. Both algorithms contain a viscous friction-like term, which aligns the velocities of neighbouring agents parallel to each other. We show that this term can be essential for reducing the inherent instabilities of such a noisy and delayed realistic system. We discuss simulation results on the stability of the control algorithms, and perform real experiments to show the applicability of the algorithms on a group of autonomous quadcopters. In our case, bio-inspiration works in two ways. On the one hand, the whole idea of trying to build and control a swarm of robots comes from the observation that birds tend to flock to optimize their behaviour as a group. On the other hand, by using a realistic simulation framework and studying the group behaviour of autonomous robots we can learn about the major factors influencing the flight of bird flocks.

Stable hovering of a jellyfish-like flying machine

Ornithopters, or flapping-wing aircraft, offer an alternative to helicopters in achieving manoeuvrability at small scales, although stabilizing such aerial vehicles remains a key challenge. Here, we present a hovering machine that achieves self-righting flight using flapping wings alone, without relying on additional aerodynamic surfaces and without feedback control. We design, construct and test-fly a prototype that opens and closes four wings, resembling the motions of swimming jellyfish more so than any insect or bird. Measurements of lift show the benefits of wing flexing and the importance of selecting a wing size appropriate to the motor. Furthermore, we use high-speed video and motion tracking to show that the body orientation is stable during ascending, forward and hovering flight modes. Our experimental measurements are used to inform an aerodynamic model of stability that reveals the importance of centre-of-mass location and the coupling of body translation and rotation. These results show the promise of flapping-flight strategies beyond those that directly mimic the wing motions of flying animals.

Head up versus head down: the costs of imprecision, unreliability, and visual clutter on cue effectiveness for display signaling

We conducted 2 experiments to investigate the clutter-scan trade-off between the cost of increasing clutter by overlaying complex information onto the forward field of view using a helmet-mounted display (HMD) and the cost of scanning when presenting this information on a handheld display. In the first experiment, this trade-off was examined in terms of the spatial accuracy of target cuing data in a relatively sparse display; in the second, the spatial accuracy of the cue was varied more radically in an information-rich display. Participants were asked to detect and identify targets hidden in the far domain while performing a monitoring task in the near domain using either an HMD or a handheld display. The results revealed that on a sparse display, the reduced scanning from the HMD presentation of cuing out-weighed the costs of clutter for cued targets, regardless of cue precision, but no benefit was found for uncued targets. When the HMD displayed task-irrelevant information, however, target detection was hindered by the extraneous clutter in the forward field of view relative to the handheld display condition, and this cost of clutter increased as the amount of data that needed to be inspected increased. Potential applications of this research include the development of design considerations for head-up displays for aviation and military applications.

Modeling and Inverse Controller Design for an Unmanned Aerial Vehicle Based on the Self-Organizing Map

The next generation of aircraft will have dynamics that vary considerably over the operating regime. A single controller will have difficulty to meet the design specifications. In this paper, a self-organizing map (SOM)-based local linear modeling scheme of an unmanned aerial vehicle (UAV) is developed to design a set of inverse controllers. The SOM selects the operating regime depending only on the embedded output space information and avoids normalization of the input data. Each local linear model is associated with a linear controller, which is easy to design. Switching of the controllers is done synchronously with the active local linear model that tracks the different operating conditions. The proposed multiple modeling and control strategy has been successfully tested in a simulator that models the LoFLYTE UAV.

The measurement of team process

The construct validity of measures of team process was evaluated using predictive, known groups and multitrait-multimethod (MTMM) validation strategies. Military air crews (N = 51) flew two simulated missions. Independent judges provided evaluations of the same six team process variables in both scenarios. An MTMM analysis of judges' ratings treating judges as a method variable showed good convergent and discriminant validity. Judges' mean ratings of the six process variables were correlated with mission effectiveness. Some process measures discriminated between student and instructor teams, thus showing discrimination between known groups. Conversely, an MTMM analysis of ratings treating scenarios as a method showed poor convergent validity. We concluded that important team process behaviors have been identified and can be rated validly but that multiple observations are necessary to assess characteristics of individual teams with any accuracy. The discussion includes implications for practice and future research.

Supporting decision making and action selection under time pressure and uncertainty: the case of in-flight icing

Operators in high-risk domains such as aviation often need to make decisions under time pressure and uncertainty. One way to support them in this task is through the introduction of decision support systems (DSSs). The present study examined the effectiveness of two different DSS implementations: status and command displays. Twenty-seven pilots (9 pilots each in a baseline, status, and command group) flew 20 simulated approaches involving icing encounters. Accuracy of the decision aid (a smart icing system), familiarity with the icing condition, timing of icing onset, and autopilot usage were varied within subjects. Accurate information from either decision aid led to improved handling of the icing encounter. However, when inaccurate information was presented, performance dropped below that of the baseline condition. The cost of inaccurate information was particularly high for command displays and in the case of unfamiliar icing conditions. Our findings suggest that unless perfect reliability of a decision aid can be assumed, status displays may be preferable to command displays in high-risk domains (e.g., space flight, medicine, and process control), as the former yield more robust performance benefits and appear less vulnerable to automation biases.

SAGE II aerosol validation: selected altitude measurements, including particle micromeasurements

Correlative aerosol measurements taken at a limited number of altitudes during coordinated field experiments are used to test the validity of particulate extinction coefficients derived from limb path solar radiance measurements taken by the Stratospheric Aerosol and Gas Experiment (SAGE) II Sun photometer. In particular, results are presented from correlative measurement missions that were conducted during January 1985, August 1985, and July 1986. Correlative sensors included impactors, laser spectrometers, and filter samplers aboard an U-2-airplane, an upward pointing lidar aboard a P-3 airplane, and balloon-borne optical particle counters (dustsondes). The main body of this paper focuses on the July 29, 1986, validation experiment, which minimized the many difficulties (e.g., spatial and temporal inhomogeneities, imperfect coincidences) that can complicate the validation process. On this day, correlative aerosol measurements taken at an altitude of 20.5 km agreed with each other within their respective uncertainties, and particulate extinction values calculated at SAGE II wavelengths from these measurements validated corresponding SAGE II values. Additional validation efforts on days when measurement and logistical conditions were much less favorable for validation are discussed in an appendix.

Design, aerodynamics and autonomy of the DelFly

One of the major challenges in robotics is to develop a fly-like robot that can autonomously fly around in unknown environments. In this paper, we discuss the current state of the DelFly project, in which we follow a top-down approach to ever smaller and more autonomous ornithopters. The presented findings concerning the design, aerodynamics and autonomy of the DelFly illustrate some of the properties of the top-down approach, which allows the identification and resolution of issues that also play a role at smaller scales. A parametric variation of the wing stiffener layout produced a 5% more power-efficient wing. An experimental aerodynamic investigation revealed that this could be associated with an improved stiffness of the wing, while further providing evidence of the vortex development during the flap cycle. The presented experiments resulted in an improvement in the generated lift, allowing the inclusion of a yaw rate gyro, pressure sensor and microcontroller onboard the DelFly. The autonomy of the DelFly is expanded by achieving (1) an improved turning logic to obtain better vision-based obstacle avoidance performance in environments with varying texture and (2) successful onboard height control based on the pressure sensor.

Attitude determination using a MEMS-based flight information measurement unit

Obtaining precise attitude information is essential for aircraft navigation and control. This paper presents the results of the attitude determination using an in-house designed low-cost MEMS-based flight information measurement unit. This study proposes a quaternion-based extended Kalman filter to integrate the traditional quaternion and gravitational force decomposition methods for attitude determination algorithm. The proposed extended Kalman filter utilizes the evolution of the four elements in the quaternion method for attitude determination as the dynamic model, with the four elements as the states of the filter. The attitude angles obtained from the gravity computations and from the electronic magnetic sensors are regarded as the measurement of the filter. The immeasurable gravity accelerations are deduced from the outputs of the three axes accelerometers, the relative accelerations, and the accelerations due to body rotation. The constraint of the four elements of the quaternion method is treated as a perfect measurement and is integrated into the filter computation. Approximations of the time-varying noise variances of the measured signals are discussed and presented with details through Taylor series expansions. The algorithm is intuitive, easy to implement, and reliable for long-term high dynamic maneuvers. Moreover, a set of flight test data is utilized to demonstrate the success and practicality of the proposed algorithm and the filter design.

Launching the AquaMAV: bioinspired design for aerial-aquatic robotic platforms

Current Micro Aerial Vehicles (MAVs) are greatly limited by being able to operate in air only. Designing multimodal MAVs that can fly effectively, dive into the water and retake flight would enable applications of distributed water quality monitoring, search and rescue operations and underwater exploration. While some can land on water, no technologies are available that allow them to both dive and fly, due to dramatic design trade-offs that have to be solved for movement in both air and water and due to the absence of high-power propulsion systems that would allow a transition from underwater to air. In nature, several animals have evolved design solutions that enable them to successfully transition between water and air, and move in both media. Examples include flying fish, flying squid, diving birds and diving insects. In this paper, we review the biological literature on these multimodal animals and abstract their underlying design principles in the perspective of building a robotic equivalent, the Aquatic Micro Air Vehicle (AquaMAV). Building on the inspire-abstract-implement bioinspired design paradigm, we identify key adaptations from nature and designs from robotics. Based on this evaluation we propose key design principles for the design of successful aerial-aquatic robots, i.e. using a plunge diving strategy for water entry, folding wings for diving efficiency, water jet propulsion for water takeoff and hydrophobic surfaces for water shedding and dry flight. Further, we demonstrate the feasibility of the water jet propulsion by building a proof-of-concept water jet propulsion mechanism with a mass of 2.6 g that can propel itself up to 4.8 m high, corresponding to 72 times its size. This propulsion mechanism can be used for AquaMAV but also for other robotic applications where high-power density is of use, such as for jumping and swimming robots.

Three-dimensional audio versus head-down traffic alert and collision avoidance system displays

The advantage of a head-up auditory display for situational awareness was evaluated in an experiment designed to measure and compare the acquisition time for capturing visual targets under two conditions: standard head-down Traffic Alert and Collision Avoidance System display and three-dimensional (3-D) audio Traffic Alert and Collision Avoidance System presentation. (The technology used for 3-D audio presentation allows a stereo headphone user to potentially localize a sound at any externalized position in 3-D auditory space). Ten commercial airline crews were tested under full-mission simulation conditions at the NASA-Ames Crew-Vehicle Systems Research Facility Advanced Concepts Flight Simulator. Scenario software generated targets corresponding to aircraft that activated a 3-D aural advisory (the head-up auditory condition) or a standard, visual-audio TCAS advisory (map display with monaural audio alert). Results showed a significant difference in target acquisition time between the two conditions, favoring the 3-D audio Traffic Alert and Collision Avoidance System condition by 500 ms.

Adaptive control of a millimeter-scale flapping-wing robot

Challenges for the controlled flight of a robotic insect are due to the inherent instability of the system, complex fluid-structure interactions, and the general lack of a complete system model. In this paper, we propose theoretical models of the system based on the limited information available from previous work and a comprehensive flight controller. The modular flight controller is derived from Lyapunov function candidates with proven stability over a large region of attraction. Moreover, it comprises adaptive components that are capable of coping with uncertainties in the system that arise from manufacturing imperfections. We have demonstrated that the proposed methods enable the robot to achieve sustained hovering flights with relatively small errors compared to a non-adaptive approach. Simple lateral maneuvers and vertical takeoff and landing flights are also shown to illustrate the fidelity of the flight controller. The analysis suggests that the adaptive scheme is crucial in order to achieve millimeter-scale precision in flight control as observed in natural insect flight.