Mustapha Mouloua

Effects of Spatial Cuing on Luminance Detectability: Psychophysical and Electrophysiological Evidence for Early Selection

Three experiments were conducted to determine whether attention-related changes in luminance detectability reflect a modulation of early sensory processing. Experiments 1 and 2 used peripheral cues to direct attention and found substantial effects of cue validity on target detectability; these effects were consistent with a sensory-level locus of selection but not with certain memory- or decision-level mechanisms. In Experiment 3, event-related brain potentials were recorded in a similar paradigm using central cues, and attention was found to produce changes in sensory-evoked brain activity beginning within the 1st 100 ms of stimulus processing. These changes included both an enhancement of sensory responses to attended stimuli and a suppression of sensory responses to unattended stimuli; the enhancement and suppression effects were isolated to different neural responses, indicating that they may arise from independent attentional mechanisms.

EFFECTS OF ADAPTIVE TASK ALLOCATION ON MONITORING OF AUTOMATED SYSTEMS

The effects of adaptive task allocation on monitoring for automation failure during multi task flight simulation were examined. Participants monitored an automated engine status task while simultaneously performing tracking and fuel management tasks over three 3D-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 participants 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 lO-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.

Mechanisms of visual-spatial attention: resource allocation or uncertainty reduction?

Many studies have found that stimuli can be discriminated more accurately at attended locations than at unattended locations, and such results have typically been taken as evidence for the hypothesis that attention operates by allocating limited perceptual processing resources to attended locations. An alternative proposal, however, is that attention acts to reduce uncertainty about target location, thereby increasing accuracy by decreasing the number of noise sources. To distinguish between these alternatives, we conducted 6 spatial cuing experiments in which target location uncertainty was eliminated. Despite the absence of uncertainty, target discriminations were more accurate at the attended location, consistent with resource allocation models. These cue validity effects were observed under a broad range of conditions, including central and peripheral cuing, but were absent at very short cue-target delay intervals.

Interaction of signal discriminability and task type in vigilance decrement

The results of recent studies suggest that perceptual sensitivity may decline over time in highevent-rate vigilance tasks either (1) when signals require successive, rather than simultaneous, discrimination or (2) when signals are difficult to discriminate from nonsignals. The joint effects of these two factors were examined in the present study. Two groups of subjects performed simultaneous- and successive-discrimination vigilance tasks requiring the discrimination of differences in line lengths at each of three levels of signal discriminabilitylow, moderate, and high. Both tasks lasted 30 min and had a high nonsignal-event rate. Perceptual sensitivity was assessed, using both parametric and nonparametric indices. For moderately or highly discriminable signals, sensitivity declined over time for the successive-discrimination task but not for the simultaneous-discrimination task. For low-discriminability signals, however, a sensitivity decrement was obtained for both tasks. These findings point to the role of the cumulative demand on attentional capacity in determining sensitivity decrement. The results are discussed in terms of attention allocation processes in high-event-rate vigilance tasks.

Human Factors in Simulation and Training

Measure twice, cut once. Although applicable to all areas of human factors research, this old adage is especially relevant to simulation and training. As a tool, simulation is an aid to the imagination; however, if incorrectly or inadequately used, it can lead to inaccurate outcomes that not only limit the possibilities, but potentially cause harm. A comprehensive overview of the topic from a human factor perspective, Human Factors in Simulation and Training not only reflects the state-of-the art, but also integrates the literature on simulation into one cohesive resource. Experts Share their Insight The editors have solicited chapters on a wide variety of topics, beginning with theory and application in areas ranging from traditional training to augmented and virtual reality. This coverage includes surface ships, submarines, naval aviation, commercial aviation, space, and medicine. The theory based section focuses on human factors aspects of simulation and training ranging from the history of simulators and training devices, to future trends in simulation from both a civilian and military perspective. The chapters expand on concepts regarding simulator usage particularly with respect to the validity and functionality of simulators as training devices. They contain in-depth discussions of specific issues, including fidelity, interfaces and control devices, transfer of training, simulator sickness, effects of motion in simulated systems, and virtual reality. As more, and more sophisticated, simulation tools and training technologies become available, a complete understanding of how to use them appropriately will be even more crucial. Elucidating theory and application, the book addresses numerous issues and concepts pertaining to human factors in simulation and training, making this volume an important addition to the bookshelf of any human factors professional.

Human-Centered Design of Unmanned Aerial Vehicles:

Technology advances and increased application of UAVs will demand greater attention to human factors concerns in design, deployment, and training.

WORKLOAD, SITUATION AWARENESS, AND TEAMING ISSUES FOR UAV/UCAV OPERATIONS

A new partnership is forming between humans and uninhabited aircraft. To augment the abilities of military forces on the ground and in the air, the US Armed Forces have developed several Unmanned Aerial Vehicles (UAVs) to work in conjunction with human pilots and enhance surveillance and combat capabilities. Even with no onboard pilot, unmanned aerial vehicles (UAVs) and combat-tailored versions (UCAVs) rely on proficient human operators on the ground for proper guidance and munitions deployment. For this reason, system designers must consider several key human factors issues in the development of functional UAV/UCAV systems. This work addresses three of these issues: workload, situation awareness, and teaming concerns. Recommendations to maximize operator efficacy, based on findings from human factors and ergonomics research, are presented as well as implications for training.

What to Automate: Addressing the Multidimensionality of Cognitive Resources Through System Design

The implementation of automation relies on the assumption that automation will reduce the operator’s cognitive demand and improve performance. However, accepted models demonstrate the multidimensionality of cognitive resources, suggesting that automation must support an appropriate resource dimension to have an appreciable effect. To evaluate this theory, the present study examined the impact of various types of automation on an unmanned ground vehicle (UGV) operator’s performance, workload, and stress. The use of a visually demanding task allowed for comparison between an auditory alert (supporting the heavily burdened visual dimension) and a driving aid (supporting action execution, a relatively unburdened cognitive dimension). Static and adaptive (fluctuating based on task demand) levels were implemented for each automation type. Those receiving auditory alerts exhibited better performance and reduced Worry, but also increased Temporal Demand and Effort relative to those receiving driving automation. Adaptive automation reduced workload for those receiving the auditory alerts, and increased workload for those receiving the driving automation. The results from this research demonstrate the need to consider the multidimensionality of the operator’s cognitive resources when implementing automation into a system. System designers should consider the type of automation necessary to support the specific cognitive resources burdened by the task.

Ergonomics of UAV/UCAV Mission Success: Considerations for Data Link, Control, and Display Issues

The United States Armed Forces are turning to Unmanned Aerial Vehicles (UAVs), and their combat-modified counterparts (UCAVs), to support human pilots and improve electronic surveillance and weapons deployment capabilities, particularly for risky suppression of enemy air-defense (SEAD) operations. Successful implementation and integration of UAVs/UCAVs into todays military requires focused attention toward human factors issues to ensure mission success and efficiency. In addition to considerations for satellite links, positive target verification, and assurance of collateral safety prior to weapon(s) launch, a primary concern is how operators interact with the UAV/UCAV system. This paper describes a portion of these concerns by presenting human factors considerations for UAV/UCAV-operator data links, vehicle control, and operator display issues. Relevant empirical findings are reviewed and implications for training and systems design are outlined.

Monitoring Automation Failures: Effects of Single and Multi-Adaptive Function Allocation

Adaptive function allocation has been proposed to allow the advantages of task automation to be realized without some of the disadvantages of “static” automation. However, few empirical studies of the efficacy of adaptive allocation have been reported. The effects of adaptive function allocation on monitoring for automation failure during multi-task flight simulation were examined in two experiments. The first study examined the use of two methods of adaptive function allocation as a possible counter-measure to automation-induced monitoring problems. Subjects were required to perform a tracking and fuel management task while monitoring an automated system monitoring task for possible failures. For the “model-based” and “performance-based” adaptive groups, a single 10-minute block of fully manual performance on the monitoring task was allocated to subjects in the middle of a session. For the control group system monitoring was automated throughout all sessions. All three groups had low probabilities of detection of automation failures for the first 40 minutes spent with automation, before the adaptive function allocation change. However, detection probabilities were higher for both adaptive groups than for the control group following the function allocation change. The second study found that multiple adaptive changes (repeated function allocation) sustained these performance benefits over a longer automation period. These results clearly indicate that adaptive function allocation can improve detection of automation failures and that the improvement can be sustained over long periods of automation cycles.