Ronald L. Boring

Shared understanding for collaborative control

This paper presents results from three experiments in which human operators were teamed with a mixed-initiative robot control system to accomplish various indoor search and exploration tasks. By assessing human workload and error together with overall performance, these experiments provide an objective means to contrast different modes of robot autonomy and to evaluate both the usability of the interface and the effectiveness of autonomous robot behavior. The first experiment compares the performance achieved when the robot takes initiative to support human driving with the opposite case when the human takes initiative to support autonomous robot driving. The utility of robot autonomy is shown through achievement of better performance when the robot is in the drivers seat. The second experiment introduces a virtual three-dimensional (3-D) map representation that supports collaborative understanding of the task and environment. When used in place of video, the 3-D map reduced operator workload and navigational error. By lowering bandwidth requirements, use of the virtual 3-D interface enables long-range, nonline-of-sight communication. Results from the third experiment extend the findings of experiment 1 by showing that collaborative control can increase performance and reduce error even when the complexity of the environment is increased and workload is distributed amongst multiple operators.

The origins of the SPAR-H method’s performance shaping factor multipliers

The Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) method has proved to be a reliable, easy-to-use method for human reliability analysis. Calculation of human error probability (HEP) rates is especially straightforward, starting with pre-defined nominal error rates for cognitive vs. action oriented tasks, and incorporating performance shaping factor (PSF) multipliers upon those nominal error rates. SPAR-H uses eight PSFs with multipliers typically corresponding to nominal, degraded, and severely degraded human performance for individual PSFs. Additionally, some PSFs feature multipliers to reflect enhanced performance. Although SPAR-H enjoys widespread use among industry and regulators, current source documents on SPAR-H such as NUREG/CR-6883 do not provide a clear account of the origin of these multipliers. The present paper redresses this shortcoming and documents the historic development of the SPAR-H PSF multipliers, from the initial use of nominal error rates, to the selection of the eight PSFs, to the mapping of multipliers to available data sources such as a Technique for Human Error Rate Prediction (THERP). Where error rates were not readily derived from THERP and other sources, expert judgment was used to extrapolate appropriate values. In documenting key background information on the multipliers, this paper provides a much needed cross-reference for human reliability practitioners and researchers of SPAR-H to validate analyses and research findings.

The Measure of human error: Direct and indirect performance shaping factors

The goal of performance shaping factors (PSFs) is to provide measures to account for human performance. PSFs fall into two categories—direct and indirect measures of human performance. While some PSFs such as “time to complete a task” are directly measurable, other PSFs, such as “fitness for duty,” can only be measured indirectly through other measures and PSFs, such as through fatigue measures. This paper explores the role of direct and indirect measures in human reliability analysis (HRA) and the implications that measurement theory has on analyses and applications using PSFs. The paper concludes with suggestions for maximizing the reliability and validity of PSFs.

Advantages and disadvantages of physiological assessment for next generation control room design

We propose using non-obtrusive physiological assessment (e.g., eye tracking,) to assess human information processing errors (e.g., loss of vigilance) and limitations (e.g., workload) for advanced energy systems early in the design process. This physiological approach for assessing risk will circumvent many limitations of current risk methodologies such as subjective rating (e.g., rater’s biases) and performance modeling (e.g., risk assessment is scripted and is based upon the individual modeler’s judgment). Key uses will be to evaluate (early in the design process) novel control room equipment and configurations as well as newly developed automated systems that will inevitably place a high information load on operators. The physiological risk assessment tool will allow better precision in pinpointing problematic design issues and will provide a “real-time” assessment of risk. Furthermore, this physiological approach would extend the state-of-the-art of human reliability methods from a “static” measure to more “dynamic.” This paper will discuss a broad range of the current popular online performance gauges as well as its advantages and disadvantages for use in next generation control room.

Bridging Human Factors and Human Reliability Analysis

Human factors (HF) and human reliability analysis (HRA) are often treated as two distinct disciplines. The former is seen under the purview of experimental psychology, while the latter is linked to an engineering approach for risk assessment. Despite this seeming separation, there exists significant overlap between these approaches, and it may be argued that the two disciplines are, in fact, more integrated than dissimilar. This paper explores the historical origins of the perceived differences between HF and HRA, discusses the seemingly disparate data end products of HF and HRA, and proposes a research framework in which the complementary nature of HF and HRA is fully realized.

A prototyping environment for research on human-machine interfaces in process control use of Microsoft WPF for microworld and distributed control system development

Operators of critical processes, such as nuclear power production, must contend with highly complex systems, procedures, and regulations. Developing human-machine interfaces (HMIs) that better support operators is a high priority for ensuring the safe and reliable operation of critical processes. Human factors engineering (HFE) provides a rich and mature set of tools for evaluating the performance of HMIs, but the set of tools for developing and designing HMIs is still in its infancy. Here we propose that Microsoft Windows Presentation Foundation (WPF) is well suited for many roles in the research and development of HMIs for process control.

Early-Stage Design and Evaluation for Nuclear Power Plant Control Room Upgrades

As control rooms are modernized with new digital systems at nuclear power plants, it is necessary to evaluate operator performance with these systems as part of a verification and validation process. While there is regulatory and industry guidance for some modernization activities, there are no well defined standard processes or predefined metrics available for assessing what is satisfactory operator interaction with new systems, especially during the early design stages. This paper proposes a framework defining the design process and metrics for evaluating human system interfaces as part of control room modernization. The process and metrics are generalizable to other applications and serve as a guiding template for utilities undertaking their own control room modernization activities.

SIG: the role of human-computer interaction in next-generation control rooms

The purpose of this CHI Special Interest Group (SIG) is to facilitate the convergence between human-computer interaction (HCI) and control room design. HCI researchers and practitioners actively need to infuse state-of-the-art interface technology into control rooms to meet usability, safety, and regulatory requirements. This SIG outlines potential HCI contributions to instrumentation and control (I&C) and automation in control rooms as well as to general control room design.

A Microworld Simulator for Process Control Research and Training

We introduce and will demonstrate a new software tool for creating simulations of simplified process control tasks—what Vincente (2000) termed microworlds—for research and training applications. This tool builds on previous software tools, such as the synthetic task environment DURESS, but provides more flexibility in simulation design, a more realistic physics model, and additional components for representing complex processes, such as auditory and visual alarms for nuclear power plants. Further, our microworld simulation tool can be used for a variety of tasks, from flexibly specifying a synthetic environment for research on a desktop computer to scaling up to large format touch displays with realistic controls typical of high-fidelity process control simulators. Potential applications of the microworld simulator include research on the cognitive engineering of human-machine interfaces used in process control, training of process control operators and other personnel, and rapid prototyping and testing of process controls and displays.

Capturing control room simulator data with the HERA System

The Human Event Repository and Analysis (HERA) system has been developed as a tool for classifying and recording human performance data extracted from primary data sources. This paper reviews the process of extracting data from simulator studies for use in HERA. Simulator studies pose unique data collection challenges, both in types and quality of data measures, but such studies are ideally suited to gather operator performance data, including the full spectrum of performance shaping factors used in a HERA analysis. This paper provides suggestions for obtaining relevant human performance data for a HERA analysis from a control room simulator study and for inputting those data in a format suitable for HERA.