Prospective Memory Performance in Simulated Air Traffic Control: Robust to Interruptions but Impaired by Retention Interval

OBJECTIVE: To examine the effects of interruptions and retention interval on prospective memory for deferred tasks in simulated air traffic control. BACKGROUND: In many safety-critical environments, operators need to remember to perform a deferred task, which requires prospective memory. Laboratory experiments suggest that extended prospective memory retention intervals, and interruptions in those retention intervals, could impair prospective memory performance. METHOD: Participants managed a simulated air traffic control sector. Participants were sometimes instructed to perform a deferred handoff task, requiring them to deviate from a routine procedure. We manipulated whether an interruption occurred during the prospective memory retention interval or not, the length of the retention interval (37-117 s), and the temporal proximity of the interruption to deferred task encoding and execution. We also measured performance on ongoing tasks. RESULTS: Increasing retention intervals (37-117 s) decreased the probability of remembering to perform the deferred task. Costs to ongoing conflict detection accuracy and routine handoff speed were observed when a prospective memory intention had to be maintained. Interruptions did not affect individuals' speed or accuracy on the deferred task. CONCLUSION: Longer retention intervals increase risk of prospective memory error and of ongoing task performance being impaired by cognitive load; however, prospective memory can be robust to effects of interruptions when the task environment provides cuing and offloading. APPLICATION: To support operators in performing complex and dynamic tasks, prospective memory demands should be reduced, and the retention interval of deferred tasks should be kept as short as possible

Prospective Memory in the Red Zone: Cognitive Control and Capacity Sharing in a Complex, Multi-Stimulus Task

© 2019 American Psychological Association. Remembering to perform a planned action upon encountering a future event requires event-based Prospective Memory (PM). PM is required in many human factors settings in which operators must process a great deal of complex, uncertain information from an interface. We study event-based PM in such an environment. Our task, which previous research has found is very demanding (Palada, Neal, Tay, & Heathcote, 2018), requires monitoring ships as they cross the ocean on a display. We applied the Prospective Memory Decision Control Model (Strickland, Loft, Remington, & Heathcote, 2018) to understand the cognitive mechanisms that underlie PM performance in such a demanding environment. We found evidence of capacity sharing between monitoring for PM items and performing the ongoing surveillance task, whereas studies of PM in simpler paradigms have not (e.g., Strickland et al., 2018). We also found that participants applied proactive and reactive control (Braver, 2012) to adapt to the demanding task environment. Our findings illustrate the value of human factors simulations to study capacity sharing between competing task processes. They also illustrate the value of cognitive models to illuminate the processes underlying adaptive behavior in complex environments

Visuomotor control, eye movements, and steering : A unified approach for incorporating feedback, feedforward, and internal models

The authors present an approach to the coordination of eye movements and locomotion in naturalistic steering tasks. It is based on recent empirical research, in particular, on driver eye movements, that poses challenges for existing accounts of how we visually steer a course. They first analyze how the ideas of feedback and feedforward processes and internal models are treated in control theoretical steering models within vision science and engineering, which share an underlying architecture but have historically developed in very separate ways. The authors then show how these traditions can be naturally (re)integrated with each other and with contemporary neuroscience, to better understand the skill and gaze strategies involved. They then propose a conceptual model that (a) gives a unified account to the coordination of gaze and steering control, (b) incorporates higher-level path planning, and (c) draws on the literature on paired forward and inverse models in predictive control. Although each of these (a–c) has been considered before (also in the context of driving), integrating them into a single framework and the authors’ multiple waypoint identification hypothesis within that framework are novel. The proposed hypothesis is relevant to all forms of visually guided locomotion.Peer reviewe

Applying psychological science to the CCTV review process: a review of cognitive and ergonomic literature

As CCTV cameras are used more and more often to increase security in communities, police are spending a larger proportion of their resources, including time, in processing CCTV images when investigating crimes that have occurred (Levesley & Martin, 2005; Nichols, 2001). As with all tasks, there are ways to approach this task that will facilitate performance and other approaches that will degrade performance, either by increasing errors or by unnecessarily prolonging the process. A clearer understanding of psychological factors influencing the effectiveness of footage review will facilitate future training in best practice with respect to the review of CCTV footage. The goal of this report is to provide such understanding by reviewing research on footage review, research on related tasks that require similar skills, and experimental laboratory research about the cognitive skills underpinning the task. The report is organised to address five challenges to effectiveness of CCTV review: the effects of the degraded nature of CCTV footage, distractions and interrupts, the length of the task, inappropriate mindset, and variability in people’s abilities and experience. Recommendations for optimising CCTV footage review include (1) doing a cognitive task analysis to increase understanding of the ways in which performance might be limited, (2) exploiting technology advances to maximise the perceptual quality of the footage (3) training people to improve the flexibility of their mindset as they perceive and interpret the images seen, (4) monitoring performance either on an ongoing basis, by using psychophysiological measures of alertness, or periodically, by testing screeners’ ability to find evidence in footage developed for such testing, and (5) evaluating the relevance of possible selection tests to screen effective from ineffective screener

Effects of Cognitive Loading on Pilots and Air Traffic Controller Performance: Implications for Neural Dynamics and Cognitive Flow

The digitized environment in aviation operations has seen marked growth and expansion as new technologies arrive and are implemented. The flight deck and air traffic control functions are two areas where growth is particularly robust. Previous work has identified the effects of compounded cognitive loading and SHELL interfaces in these work environments, and the potential consequences when relief or collaborative resource management is not employed effectively. This paper examines the relationship of cognitive loading in the context of cognitive flow to identify potential areas where neural metrics might aid in a better understanding of the dynamics to determine thresholds of overload. Application of the Triple- Network Model of neural regulation dynamics and Polyvagal Theory are explored for potential relationships to compromised situation awareness and working memory constraints. Conclusions indicate that when cognitive flow is disrupted, cognitive processing loads on working memory expand exponentially and rapidly reach a plateau that inhibits safe performance. Implications suggest a more focused effort in systems and training to address neural metrics and cognitive processing rates

DeepCSO: Forecasting of Combined Sewer Overflow at a Citywide Level using Multi-task Deep Learning

Combined Sewer Overflow (CSO) is a major problem to be addressed by many cities. Understanding the behavior of sewer system through proper urban hydrological models is an effective method of enhancing sewer system management. Conventional deterministic methods, which heavily rely on physical principles, is inappropriate for real-time purpose due to their expensive computation. On the other hand, data-driven methods have gained huge interests, but most studies only focus on modeling a single component of the sewer system and supply information at a very abstract level. In this paper, we proposed the DeepCSO model, which aims at forecasting CSO events from multiple CSO structures simultaneously in near real time at a citywide level. The proposed model provided an intermediate methodology that combines the flexibility of data-driven methods and the rich information contained in deterministic methods while avoiding the drawbacks of these two methods. A comparison of the results demonstrated that the deep learning based multi-task model is superior to the traditional methods

Hysteresis Effects In Driving

This dissertation presents two studies examining the interaction between workload history and driver mental workload. The first experiment focuses on testing for the presence of a hysteresis effect in the driving task. The second experiment examines the proposition that cueing impending periods of higher task demand can reduce the impact of any such potential hysteresis effects. Thirty-two licensed drivers served as participants and all served in both studies. Using the directions provided by a Heads-Up-Display navigation system, participants followed a pre-set route in the simulated environment. At specified points within the drive, the navigation system would purposefully fail which required drivers to relay a ten digit alphanumeric error code to a remote operator in order to reset the system. Results indicated that this increase in task demand from the navigation system\u27s failure leads to a significant increase in perceived mental workload as compared to pre-failure periods. This increase in driver mental workload was not significantly reduced by the time the drive ended, indicating the presence of a hysteresis effect. In the second experiment, the navigation system provided a completely reliable visual warning before failure. Results indicate that cueing had neither an effect on perceived mental workload, nor any ameliorating effect on the hysteretic type effect seen in mental workload recovery. The conclusion of these findings being that the overall safety and efficiency of the surface transportation system would likely improve by designs which accommodate the periods immediately following a reduction in stress. Whether from leaving high demand areas such as work zones or in the period immediately after using a in-car information device such as a GPS or a cell phone, these post-high workload periods are associated with increased variability in driver inputs and levels of mental workload

Effects of Stereoscopic 3D Digital Radar Displays on Air Traffic Controller Performance

Air traffic controllers are responsible for directing air traffic based upon decisions made from traffic activity depicted on 2Dimensional (2D) radar displays. Controllers must identify aircraft and detect potential conflicts while simultaneously developing and executing plans of action to ensure safe separation is maintained. With a nearly 100% increase in traffic expected within the next decade (FAA, 2012a), controllers\u27 abilities to rapidly interpret spacing and maintain awareness for longer durations with increased workload will become increasingly imperative to safety. The current display design spatially depicts an aircraft\u27s position relative to the controller\u27s airspace as well as speed, altitude, and direction in textual form which requires deciphering and arithmetic to determine vertical separation. Since vertical separation is as imperative to flight safety as lateral separation, affording the controller an intuitive design for determining spacing without mental model creation is critical to reducing controller workload, and increasing awareness and efficiency. To examine this potential, a stereoscopic radar workstation simulator was developed and field-tested with 35 USAF controllers. It presented a view similar to traditional radar displays, (i.e. top-down), however, it depicted altitude through the use of 3D stereoscopic disparity, permitting vertical separation to be visually represented