Effects of Automation for Emergency Operating Procedures on Human Performance in a Nuclear Power Plant

ABSTRACT

The digitization of the control systems in the main control room of a nuclear power plant has changed the operators' role in coping with accidents and has thus brought about new human factor problems. This article focuses on the procedures that are used for guiding the emergency operating procedures in a nuclear power plant, and experimentally investigates the effects of the digitization of procedures on operators' mental workload and situation awareness. In these experiments, the procedures at three different levels of automation, namely, paper-based procedures (PBPs), electronic procedures (EPs), and computer-based procedures (CBPs), are used as the independent variables. According to the experimental results, using these procedures at a high level of automation enables the operator to exhibit favorable operational performance with a decreased mental workload; however, the operator's situation awareness (SA) is decreased. The research results presented here can provide a reference level for optimally setting the level of automation of the emergency operating procedures in a nuclear power plant and provide support for the optimization of a corresponding HRA (Human Reliability Analysis) model.

Effects of automation reliability on error detection and attention to auditory stimuli in a multi-tasking environment

Automated aids are engineered to support operators' decision-making in complex and task-saturated environments, alerting them of system status and critical incidents. However, even the most advanced technologies are susceptible to failure. Monitoring imperfect automated systems poses unique challenges related to operator attention and workload. This study empirically examined the effect of unreliable automation on monitoring performance and responses to auditory stimuli in a multi-tasking environment. Participants completed an experimental trial consisting of four flight-related tasks while monitoring for automation failures at one of three levels of automation reliability. Participants in a high reliability condition responded more quickly and frequently to auditory messages. No performance differences were found in system monitoring performance between reliability conditions. These results are relevant to the design of automated system and delivery of automated alerts, and they have implications for operator attention allocation strategies in multi-tasking environments.

Dangerous intersections? A review of studies of fatigue and distraction in the automated vehicle

The impacts of fatigue on the vehicle driver may change with technological advancements including automation and the increasing prevalence of potentially distracting in-car systems. This article reviews the authors' simulation studies of how fatigue, automation, and distraction may intersect as threats to safety. Distinguishing between states of active and passive fatigue supports understanding of fatigue and the development of countermeasures. Active fatigue is a stress-like state driven by overload of cognitive capabilities. Passive fatigue is produced by underload and monotony, and is associated with loss of task engagement and alertness. Our studies show that automated driving reliably elicits subjective symptoms of passive fatigue and also loss of alertness that persists following manual takeover. Passive fatigue also impairs attention and automation use in operators of Remotely Piloted Vehicles (RPVs). Use of in-vehicle media has been proposed as a countermeasure to fatigue, but such media may also be distracting. Studies tested whether various forms of phone-based media interacted with automation-induced fatigue, but effects were complex and dependent on task configuration. Selection of fatigue countermeasures should be guided by an understanding of the form of fatigue confronting the operator. System design, regulation of level of automation, managing distraction, and selection of fatigue-resilient personnel are all possible interventions for passive fatigue, but careful evaluation of interventions is necessary prior to deployment.

Training Techniques for Visual Search in Complex Task Environments

OBJECTIVE

The goal for this study was to evaluate several visual search training techniques in an unmanned aerial vehicle (UAV) simulated task environment.

BACKGROUND

Operators controlling remote unmanned vehicles often must perform complex visual search tasks (e.g., target search). These tasks may pose substantial demands on the operator due to various environmental factors. Visual search training may reduce errors and mitigate stress, but the most effective form of training has not been determined.

METHODS

Participants were assigned to one of four training conditions: target, cue, visual scanning, or control. After the training, the effectiveness of the training techniques was tested during a 30-minute simulated UAV flight. A secondary task manipulation was included to further simulate the demands of a realistic UAV control and target search task. Subjective stress and fatigue were also assessed.

RESULTS

Target training produced superior target search performances in more hits and fewer false alarms (FAs) when compared to the control condition. The visual scanning and cue trainings were moderately effective. Only target training performance was vulnerable to the secondary task load. The task was stressful, but training did not mitigate stress response.

CONCLUSION

Training participants on the target and the cue appearance as well as active scanning of the visual field is promising for promoting effective target search for this simulated UAV environment.

APPLICATION

These training techniques could be used in preparation for intelligence, surveillance, and reconnaissance (ISR) missions that involve target search, especially where target appearance change is likely.