Current Search:   Adaptive Automation (x)

View All Items

  • CSV Spreadsheet
(1 - 4 of 4)
Comparing Types of Adaptive Automation within a Multi-Tasking Environment
Title
Comparing Types of Adaptive Automation within a Multi-Tasking Environment.
Creator
Taylor, Grant, Szalma, James, Hancock, Peter, Mouloua, Mustapha, Reinerman, Lauren, University of Central Florida
Abstract / Description
Throughout the many years of research examining the various effects of automation on operator performance, stress, workload, etc., the focus has traditionally been on the level of automation, and the invocation methods used to alter it. The goal of the current study is to instead examine the utilization of various types of automation with the goal of better meeting the operator's cognitive needs, thus improving their performance, workload, and stress. The task, control of a simulated unmanned...
Show moreThroughout the many years of research examining the various effects of automation on operator performance, stress, workload, etc., the focus has traditionally been on the level of automation, and the invocation methods used to alter it. The goal of the current study is to instead examine the utilization of various types of automation with the goal of better meeting the operator's cognitive needs, thus improving their performance, workload, and stress. The task, control of a simulated unmanned robotic system, is designed to specifically stress the operator's visual perception capabilities to a greater degree. Two types of automation are implemented to support the operator's performance of the task: an auditory beep aid intended to support visual perception resources, and a driving aid automating control of the vehicle's navigation, offloading physical action execution resources. Therefore, a comparison can be made between types of automation intended to specifically support the mental dimension that is under the greatest demand (the auditory beep) against those that do not (the driving automation). An additional evaluation is made to determine the benefit of adaptively adjusting the level of each type of automation based on the current level of task demand, as well as the influence of individual differences in personality.Results indicate that the use of the auditory beep aid does improve performance, but also increases Temporal Demand and Effort. Use of driving automation appears to disengage the operator from the task, eliciting a vigilance response. Adaptively altering the level of automation to meet task demands has a mixed effect on performance and workload (reducing both) when the auditory beep automation is used. However, adaptive driving automation is clearly detrimental, causing an increase in workload while decreasing performance. Higher levels of Neuroticism are related to poorer threat detection performance, but personality differences show no indication of moderating the effects of either of the experimental manipulations. The results of this study show that the type of automation implemented within an environment has a considerable impact on the operator, in terms of performance as well as cognitive/emotional state.
Show less
Date Issued
2012
Identifier
CFE0004340, ucf:49414
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0004340
Objectively Defining Scenario Complexity: Towards Automated, Adaptive Scenario-Based Training
Title
Objectively Defining Scenario Complexity: Towards Automated, Adaptive Scenario-Based Training.
Creator
Dunn, Robert, Sivo, Stephen, Hoffman, Bobby, Hartshorne, Richard, Bowers, Clint, University of Central Florida
Abstract / Description
Effective Scenario-Based Training (SBT) is sequenced in an efficient trajectory from novice to mastery and is well-grounded in pedagogically sound instructional strategies and learning theory. Adaptive, automated SBT attempts to sequence scenarios according to the performance of the student and implement the sequence without human agency. The source of these scenarios may take the form of a matrix constructed by Instructional Systems Designers (ISD), software engineers or trainers. The domain...
Show moreEffective Scenario-Based Training (SBT) is sequenced in an efficient trajectory from novice to mastery and is well-grounded in pedagogically sound instructional strategies and learning theory. Adaptive, automated SBT attempts to sequence scenarios according to the performance of the student and implement the sequence without human agency. The source of these scenarios may take the form of a matrix constructed by Instructional Systems Designers (ISD), software engineers or trainers. The domain being instructed may contain procedures or concepts that are easily differentiated thus allowing quick and accurate determination of difficulty. In this instance, the sequencing of the SBT is relatively simple. However, in complex, domain-integrated instructional environments accurate and efficient sequencing may be extremely difficult as ISD, software engineers and trainers, without an objective means to calculate a scenario's complexity must rely on subjectivity. In the Military, where time, fiscal and manpower constraints may lead to ineffective, inefficient and, perhaps, negative training SBT is a growing alternative to live training due to the significant cost avoidance demonstrated by such systems as the United States Marine Corps' (USMC) Abrams Main Battle Tank (M1A1) Advanced Gunnery Training System (AGTS). Even as the practice of simulation training grows, leadership such as the Government Accountability Office asserts that little has been done to demonstrate simulator impact on trainee proficiency. The M1A1 AGTS instructional sub system, the Improved Crew Training Program (ICTP), employs an automated matrix intended to increase Tank Commander (TC) and Gunner (GNR) team proficiency. This matrix is intended to guide the team along a trajectory of ever-increasing scenario difficulty. However, as designed, the sequencing of the matrix is based on subjective evaluation of difficulty, not on empirical or objective calculations of complexity. Without effective, automated SBT that adapts to the performance of the trainee, gaps in combat readiness and fiscal responsibility could grow large.In 2010, the author developed an algorithm intended to computationally define scenario complexity (Dunne, Schatz, Fiore, Martin (&) Nicholson, 2010) and conducted a proof of concept study to determine the algorithm's effectiveness (Dunne, Schatz, Fiore, Nicholson (&) Fowlkes, 2010). Based on results of that study, and follow-on analysis, revisions were made to that Scenario Complexity (SC) algorithm. The purpose of this research was to examine the efficacy of the revised SC algorithm to enable Educators and Trainers, ISDs, and software engineers to objectively and computationally define SC. The research process included a period of instruction for Subject Matter Experts (SME) to receive instruction on how to identify the base variables that comprise SC. Using this knowledge SMEs then determined the values of the scenarios base variables. Once calculated, these values were ranked and compared to the ICTP matrix sequence.Results indicate that the SMEs were very consistent in their ratings of the items across scenario base variables. Due to the highly proceduralized process underlying advanced gunnery skills, this high degree of agreement was expected. However, the significant lack of correlation to the matrix sequencing is alarming and while a recent study has shown the AGTS to increase TC and GNR team proficiency (PM TRASYS, 2014a), this research's findings suggests that redesign of the ICTP matrix is in order.
Show less
Date Issued
2014
Identifier
CFE0005789, ucf:50062
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0005789
Simulation-Based Cognitive Workload Modeling and Evaluation of Adaptive Automation Invoking and Revoking Strategies
Title
Simulation-Based Cognitive Workload Modeling and Evaluation of Adaptive Automation Invoking and Revoking Strategies.
Creator
Rusnock, Christina, Geiger, Christopher, Karwowski, Waldemar, Xanthopoulos, Petros, Reinerman, Lauren, University of Central Florida
Abstract / Description
In human-computer systems, such as supervisory control systems, large volumes of incoming and complex information can degrade overall system performance. Strategically integrating automation to offload tasks from the operator has been shown to increase not only human performance but also operator efficiency and safety. However, increased automation allows for increased task complexity, which can lead to high cognitive workload and degradation of situational awareness. Adaptive automation is...
Show moreIn human-computer systems, such as supervisory control systems, large volumes of incoming and complex information can degrade overall system performance. Strategically integrating automation to offload tasks from the operator has been shown to increase not only human performance but also operator efficiency and safety. However, increased automation allows for increased task complexity, which can lead to high cognitive workload and degradation of situational awareness. Adaptive automation is one potential solution to resolve these issues, while maintaining the benefits of traditional automation. Adaptive automation occurs dynamically, with the quantity of automated tasks changing in real-time to meet performance or workload goals. While numerous studies evaluate the relative performance of manual and adaptive systems, little attention has focused on the implications of selecting particular invoking or revoking strategies for adaptive automation. Thus, evaluations of adaptive systems tend to focus on the relative performance among multiple systems rather than the relative performance within a system.This study takes an intra-system approach specifically evaluating the relationship between cognitive workload and situational awareness that occurs when selecting a particular invoking-revoking strategy for an adaptive system. The case scenario is a human supervisory control situation that involves a system operator who receives and interprets intelligence outputs from multiple unmanned assets, and then identifies and reports potential threats and changes in the environment. In order to investigate this relationship between workload and situational awareness, discrete event simulation (DES) is used. DES is a standard technique in the analysis of systems, and the advantage of using DES to explore this relationship is that it can represent a human-computer system as the state of the system evolves over time. Furthermore, and most importantly, a well-designed DES model can represent the human operators, the tasks to be performed, and the cognitive demands placed on the operators. In addition to evaluating the cognitive workload to situational awareness tradeoff, this research demonstrates that DES can quite effectively model and predict human cognitive workload, specifically for system evaluation.This research finds that the predicted workload of the DES models highly correlates with well-established subjective measures and is more predictive of cognitive workload than numerous physiological measures. This research then uses the validated DES models to explore and predict the cognitive workload impacts of adaptive automation through various invoking and revoking strategies. The study provides insights into the workload-situational awareness tradeoffs that occur when selecting particular invoking and revoking strategies. First, in order to establish an appropriate target workload range, it is necessary to account for both performance goals and the portion of the workload-performance curve for the task in question. Second, establishing an invoking threshold may require a tradeoff between workload and situational awareness, which is influenced by the task's location on the workload-situational awareness continuum. Finally, this study finds that revoking strategies differ in their ability to achieve workload and situational awareness goals. For the case scenario examined, revoking strategies based on duration are best suited to improve workload, while revoking strategies based on revoking thresholds are better for maintaining situational awareness.
Show less
Date Issued
2013
Identifier
CFE0004927, ucf:49607
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0004927
OPTIMIZING THE DESIGN OF MULTIMODAL USER INTERFACES
Title
OPTIMIZING THE DESIGN OF MULTIMODAL USER INTERFACES.
Creator
Reeves, Leah, Stanney, Kay, University of Central Florida
Abstract / Description
Due to a current lack of principle-driven multimodal user interface design guidelines, designers may encounter difficulties when choosing the most appropriate display modality for given users or specific tasks (e.g., verbal versus spatial tasks). The development of multimodal display guidelines from both a user and task domain perspective is thus critical to the achievement of successful human-system interaction. Specifically, there is a need to determine how to design task information...
Show moreDue to a current lack of principle-driven multimodal user interface design guidelines, designers may encounter difficulties when choosing the most appropriate display modality for given users or specific tasks (e.g., verbal versus spatial tasks). The development of multimodal display guidelines from both a user and task domain perspective is thus critical to the achievement of successful human-system interaction. Specifically, there is a need to determine how to design task information presentation (e.g., via which modalities) to capitalize on an individual operator's information processing capabilities and the inherent efficiencies associated with redundant sensory information, thereby alleviating information overload. The present effort addresses this issue by proposing a theoretical framework (Architecture for Multi-Modal Optimization, AMMO) from which multimodal display design guidelines and adaptive automation strategies may be derived. The foundation of the proposed framework is based on extending, at a functional working memory (WM) level, existing information processing theories and models with the latest findings in cognitive psychology, neuroscience, and other allied sciences. The utility of AMMO lies in its ability to provide designers with strategies for directing system design, as well as dynamic adaptation strategies (i.e., multimodal mitigation strategies) in support of real-time operations. In an effort to validate specific components of AMMO, a subset of AMMO-derived multimodal design guidelines was evaluated with a simulated weapons control system multitasking environment. The results of this study demonstrated significant performance improvements in user response time and accuracy when multimodal display cues were used (i.e., auditory and tactile, individually and in combination) to augment the visual display of information, thereby distributing human information processing resources across multiple sensory and WM resources. These results provide initial empirical support for validation of the overall AMMO model and a sub-set of the principle-driven multimodal design guidelines derived from it. The empirically-validated multimodal design guidelines may be applicable to a wide range of information-intensive computer-based multitasking environments.
Show less
Date Issued
2007
Identifier
CFE0001636, ucf:47237
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0001636