Development of a Human Performance Model of a UAV Sensor Operator: Lessons Learned

2005 ◽  
Author(s):  
Michael A. Petkosek ◽  
Lamar Warfield ◽  
Thomas R. Carretta
Keyword(s):  
Human Performance ◽  
Performance Model ◽  
Lessons Learned

Validating Human Performance Models: Building a House without Bricks

2020 ◽  
Vol 64 (1) ◽  
pp. 1511-1514
Author(s):  
Richard Steinberg ◽  
Raytheon Company ◽  
Alice Diggs ◽  
Raytheon Company ◽  
Jade Driggs
Keyword(s):  
Air Force ◽  
Human Performance ◽  
Control Program ◽  
Real Data ◽  
Performance Model ◽  
Force Model ◽  
Performance Models ◽  
Actual System ◽  
Support Design ◽  
Trade Offs

Verification and validation (V&V) for human performance models (HPMs) can be likened to building a house with no bricks, since it is difficult to obtain metrics to validate a model when the system is still in development. HPMs are effective for performing trade-offs between the human system designs factors including number of operators needed, the role of automated tasks versus operator tasks, and member task responsibilities required to operate a system. On a recent government contract, our team used a human performance model to provide additional analysis beyond traditional trade studies. Our team verified the contractually mandated staff size for using the system. This task demanded that the model have sufficient fidelity to provide information for high confidence staffing decisions. It required a method for verifying and validating the model and its results to ensure that it accurately reflected the real world. The situation caused a dilemma because there was no actual system to gather real data to use to validate the model. It is a challenge to validate human performance models, since they support design decisions prior to system. For example, crew models are typically inform the design, staffing needs, and the requirements for each operator’s user interface prior to development. This paper discusses a successful case study for how our team met the V&V challenges with the US Air Force model accreditation authority and successfully accredited our human performance model with enough fidelity for requirements testing on an Air Force Command and Control program.

Human performance model support for a human-centric design process

2000 ◽  
Author(s):  
Gwendolyn E. Campbell ◽  
Janis A. Cannon-Bowers
Keyword(s):  
Design Process ◽  
Human Performance ◽  
Performance Model ◽  
Model Support

A Fuzzy-Based Approach to Support Decision Making in Complex Military Environments

2016 ◽  
Vol 12 (1) ◽  
pp. 1-30 ◽  
Author(s):  
Timothy P. Hanratty ◽  
E. Allison Newcomb ◽  
Robert J. Hammell II ◽  
John T. Richardson ◽  
Mark R. Mittrick
Keyword(s):  
Decision Making ◽  
Cyber Security ◽  
Human Performance ◽  
Performance Model ◽  
Military Intelligence ◽  
Conceptual Information ◽  
System Architectures ◽  
Cyber Intelligence ◽  
Soft Computing Techniques ◽  
The Military

Data for military intelligence operations are increasing at astronomical rates. As a result, significant cognitive and temporal resources are required to determine which information is relevant to a particular situation. Soft computing techniques, such as fuzzy logic, have recently been applied toward decision support systems to support military intelligence analysts in selecting relevant and reliable data within the military decision making process. This article examines the development of one such system and its evaluation using a constructive simulation and human performance model to provided critical understanding of how this conceptual information system might interact with personnel, organizational, and system architectures. In addition, similarities between military intelligence analysts and cyber intelligence analysts are detailed along with a plan for transitioning the current fuzzy-based system to the cyber security domain.

Workload Warriors: Lessons Learned from a Decade of Mental Workload Prediction Using Human Performance Modeling

2009 ◽  
Vol 53 (12) ◽  
pp. 819-823 ◽  
Author(s):  
Diane Kuhl Mitchell ◽  
Charneta Samms
Keyword(s):  
Human Behavior ◽  
Human Performance ◽  
Performance Modeling ◽  
Mental Workload ◽  
Lessons Learned ◽  
Experimental Conditions ◽  
Workload Prediction ◽  
Army Research Laboratory ◽  
Performance Predictions ◽  
Concept Vehicle

For at least a decade, researchers at the Army Research Laboratory (ARL) have predicted mental workload using human performance modeling (HPM) tools, primarily IMPRINT. During this timeframe their projects have matured from simple models of human behavior to complex analyses of the interactions of system design and human behavior. As part of this maturation process, the researchers learned: 1) to develop a modeling question that incorporates all aspects of workload, 2) to determine when workload is most likely to affect performance, 3) to build multiple models to represent experimental conditions, 4) to connect performance predictions to an overall mission or system capability, and 5) to format results in a clear, concise format. By implementing the techniques they developed from these lessons learned, the researchers have had an impact on major Army programs with their workload predictions. Specifically, they have successfully changed design requirements for future concept Army vehicles, substantiated manpower requirements for fielded Army vehicles, and made Soldier workload the number one item during preliminary design review for a major Army future concept vehicle program. The effective techniques the ARL researchers developed for their IMPRINT projects are applicable to other HPM tools. In addition, they can be used by students and researchers who are doing human performance modeling projects and are confronted with similar problems to help them achieve project success.

Accident at Fukushima Dai-Ichi Nuclear Power Plant: Lessons Learned for the Czech Republic

2014 ◽  
Author(s):  
Ladislav Vesely ◽  
Vaclav Dostal
Keyword(s):  
Czech Republic ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Human Performance ◽  
Lessons Learned ◽  
Injection System ◽  
Human Errors ◽  
The Czech Republic ◽  
Main Error

Accident at Fukushima Dai-Ichi nuclear power plant significantly affected the nuclear industry at time when everybody was expecting the so called nuclear renaissance. There is no question that the accident has at least slowed it down. Research into this accident is taking place all over the world. In this paper we present the findings of research on Fukushima nuclear power plant accident in relation to the Czech Republic. The paper focuses on the analysis of human performance during the accident. Lessons learned from the accident and main human errors are presented. First the brief factors affecting the human performance are discussed. They are followed by the short description of activities on units 1–3. The key human errors in the accident mitigation are then identified. On unit 1 the main error is wrong understanding and operation of isolation condenser. On unit 2 the main errors were unsuccessful depressurization with subsequent delay of coolant injection. On unit 3 the main error is the shutdown of high pressure cooling injection system without first confirming that different means of cooling are available. These errors lead to fuel damage. On unit 1 the fuel damage was probably impossible to prevent, however on unit 2 and 3 it could be probably prevented. The lessons learned for the Czech Republic were presented. They can be summarizes as follows: be sure that plant personnel can and knows how to monitor and operate the crucial plant components, be sure that the procedures on how to fulfill the critical safety functions are available in the symptomatic manner for situations when there is no power available at the plant, train personnel for these situations and have sufficient human resource available for these situations.

Development of Accidental Scenarios Involving Human Errors for Risk Assessment in Restricted Waters

2020 ◽  
Author(s):  
Danilo Taverna Martins Pereira de Abreu ◽  
Marcos Coelho Maturana ◽  
Marcelo Ramos Martins
Keyword(s):  
Human Error ◽  
Human Performance ◽  
Typical Feature ◽  
Performance Model ◽  
Traffic Density ◽  
Technical Failure ◽  
Event Tree ◽  
Analysis Model ◽  
Event Tree Analysis ◽  
Tree Analysis

Abstract The navigation in restricted waters imposes several challenges when compared to open sea navigation. Smaller dimensions, higher traffic density and the dynamics of obstacles such as sandbanks are examples of contributors to the difficulty. Due to these aspects, local experienced maritime pilots go onboard in order to support the ship’s crew with their skills and specific regional knowledge. Despite these efforts, several accidents still occur around the world. In order to contribute to a better understanding of the events composing accidental sequences, this paper presents a hybrid modelling specific for restricted waters. The main techniques used are the fault tree analysis and event tree analysis. The former provides a framework to investigate the causes, while the latter allows modelling the sequence of actions necessary to avoid an accident. The models are quantified using statistical data available in the literature and a prospective human performance model developed by the Technique for Early Consideration of Human Reliability (TECHR). The results include combined estimates of human error probabilities and technical failure probabilities, which can be used to inform the causation factor for a waterway risk analysis model. In other words, given that the ship encounters a potential accidental scenario while navigating, the proposed models allow computing the failure probability that of the evasive actions sequence. The novelty of this work resides on the possibility of explicitly considering dynamicity and recovery actions when computing the causation factor, what is not a typical feature of similar works. The results obtained were compared with several results available in the literature and have been shown to be compatible.

Development of a Baseline Workload Model for Future Submarine Sonar Crewing Analysis

2016 ◽  
Vol 60 (1) ◽  
pp. 670-674
Author(s):  
Wenbi Wang
Keyword(s):  
Human Performance ◽  
Discrete Event ◽  
Performance Model ◽  
Task Demand ◽  
Event Simulation ◽  
Sonar System ◽  
Performance Benchmarks ◽  
Specific Contact ◽  
Assignment Scheme ◽  
Operator Workload

A computational human performance model was developed to analyze sonar operator workload using the legacy sonar system on the Royal Canadian Navy’s Victoria-Class Submarine. The paper describes key components of the model, including a task network for representing operator activities, the Visual, Auditory, Cognitive and Psychomotor (VACP) algorithm for characterizing task demand, and a discrete-event simulation for predicting operator workload. Results from a simulation experiment revealed high levels of task demand imposed by the adopted mission scenario and an uneven distribution of workload among four sonar operators under a specific contact assignment scheme. The results establish a set of performance benchmarks that will be used for evaluating workload predictions made by a future model of a new sonar system, supporting quantifiable assessment of crewing options for the future sonar system.

Development of restoration system based on human performance model

1996 ◽  
Vol 117 (4) ◽  
pp. 34-45 ◽  
Author(s):  
Jun'Ichi Shinohara ◽  
Jun'Ichi Nagata ◽  
Hideki Saitoh ◽  
Isao Kozakai ◽  
Azuma Ohuchi ◽  
...  
Keyword(s):  
Human Performance ◽  
Performance Model
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