Situation awareness-based agent transparency for human-autonomy teaming effectiveness

Chen, Jessie Y. C.; Barnes, Michael; Wright, Julia L.; Stowers, Kimberly; Lakhmani, Shan

doi:10.1117/12.2263194

Cited by 42 publications

(57 citation statements)

References 18 publications

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“…Multiple studies have indicated the specific benefits of conveying uncertainty or reliability information of automated systems to human operators (Beller, Heesen, & Vollrath, 2013;Chen et al, 2018;Helldin, Falkman, Riveiro, & Davidsson, 2013;Mercado et al, 2016). In a driving context, Beller, Heesen & Vollrath (2013) investigated the impact of displaying a schematised uncertain face in the instrument cluster in unclear situations.…”

Section: Uncertainty Communication Methodsmentioning

confidence: 99%

Automation transparency: implications of uncertainty communication for human-automation interaction and interfaces

et al. 2019

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words)Operators of highly automated driving systems may exhibit behaviour characteristic for overtrust issues due to an insufficient awareness of automation fallibility. Consequently, situation awareness in critical situations is reduced and safe driving performance following emergency takeovers is impeded. A driving simulator study was used to assess the impact of dynamically communicating system uncertainties on monitoring, trust, workload, takeovers, and physiological responses. The uncertainty information was conveyed visually using a stylised heart beat combined with a numerical display and users were engaged in a visual search task.Multilevel analysis results suggest that uncertainty communication helps operators calibrate their trust and gain situation awareness prior to critical situations, resulting in safer takeovers.Additionally, eye tracking data indicate that operators can adjust their gaze behaviour in correspondence with the level of uncertainty. However, conveying uncertainties using a visual display significantly increases operator workload and impedes users in the execution of nondriving related tasks. Keywords: vehicle ergonomics; attitudes and behaviour; attention and vigilance; humancomputer-interaction; information displaysPractitioner summary (50 words): This paper illustrates how the communication of system uncertainty information helps operators calibrate their trust in automation and, consequently, gain situation awareness. Multilevel analysis results of a driving simulator study affirm the benefits for trust calibration and highlight that operators adjust their behaviour according to multiple uncertainty levels.

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Section: Uncertainty Communication Methodsmentioning

confidence: 99%

Automation transparency: implications of uncertainty communication for human-automation interaction and interfaces

et al. 2019

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“…In addition, studies regarding automation have focused at how to reduce workload (Earl L Wiener, 1985;Edwards, Homola, Mercer, & Claudatos, 2017), decrease vigilance (Earl L. Wiener & Curry, 1980;Earl L Wiener, 1987), and to decrease confusion about responsibilities between automation and operator (Farrell, 1987) to name a few. The research around automation has also focused on trust (Muir, 1994;Bonini, Jackson, & McDonald, 2001;Eurocontrol, 2003;de Visser et al, 2016), conformance (C. Westin, Borst, & Hilburn, 2016), complacency (Parasuraman, Molloy, & Singh, 1993;Parasuraman & Manzey, 2010), and transparency (Christoffersen & Woods, 2002;Chen, Barnes, Wright, Stowers, & Lakhmani, 2017;C. A. Westin, Palmerius, Johansson, & Lundberg, 2019).…”

Section: Automationmentioning

confidence: 99%

Human-automation teamwork : Current practices and future directions in air traffic control

Svensson

2020

Linköping Studies in Science and Technology. Dissertations

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This dissertation explores the topic of human-automation teamwork in Air Traffic Control (ATC). ATC is a high stakes environment where complex automation is being introduced while the human operator has the legal responsibility. With increasing demands on productivity in various industries (as also in ATC), automation is introduced for efficiency, maintaining safety, and to keep the workload of the human operator within acceptable limits. However, previous research has shown that automation may cause negative effects on the human operator and performance, such as forcing the operator out of the control loop, which might lead to problems or confusion. Previous research suggests a need for strengthening human-automation collaboration where automation is seen as a team member to keep the operator in the loop. In order to achieve such teamwork, the design of the automation needs to be human-centred, i.e. that the automation is designed for the underlying need of the operator.The aim of this dissertation is to explore teamwork in ATC from several angles to understand how the air traffic controllers are working in current ATC environments and how automation could be designed to support humanautomation teamwork. The included studies rely on interviews, simulations, and questionnaires, all with operational air traffic controllers as participants.The results indicate that for both human-human teamwork and humanautomation teamwork, teamwork factors such as adaptability and mutual performance monitoring (knowing what the other team members are doing) are important for the work performance in current ATC environments, where mutual performance monitoring is especially important during stressful situations.When designing automation, lessons learned from human-human teamwork should be considered. The work within the scope of this dissertation identifies and concerns two human-automation teamwork aspects: boundary awareness and implicit communication. These are proposed to support the operator's knowledge about the automation and the communication flow between the iv operator and the automation. Boundary awareness is the operator's knowledge of the automation's abilities, its boundaries (what it can or cannot manage), and about consequences if it would go outside of these boundaries. Implicit communication is the unspoken or implied small cues that the operator and the automation can use to communicate with each other. It is proposed that implicit communication can be based on the work patterns of the operator. The knowledge gained through the work in this dissertation can be used as a foundation for further research and design of automation regarding operator knowledge about the automation boundaries and the communication within the team. v vii INCLUDED PUBLICATIONS

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“…Since the SAT model was first introduced in 2014, progress in artificial intelligence and in the capabilities of autonomous systems has continued to advance. To capitalize on these advances in machine learning and their potential applications in mixedinitiative teaming, we have expanded the SAT model by incorporating aspects of Teamwork transparency and Bidirectional communications between human and machine agents [1]. To facilitate the creation and maintenance of a shared understanding between the human and machine agents, the machine must communicate not only taskwork information (e.g., task procedures, likely scenarios, environmental constraints) but teamwork-related information as well (e.g., role interdependencies, interaction patterns, teammates' abilities).…”

Section: Teamwork Transparencymentioning

confidence: 99%

“…We developed the SA-based Agent Transparency (SAT) [1] model-based on the theory of situation awareness (SA) [2], the Beliefs-Desires-Intentions Agent Framework [3], and other relevant previous work [4][5]-to support human operator's SA of the mission environment involving the autonomous agent ( Fig. 1).…”

Section: Introductionmentioning

confidence: 99%

“…1). Agent transparency is defined as the "quality of an interface pertaining to its abilities to afford an operator's comprehension about an intelligent agent's intent, performance, future plans, and reasoning process" [1]. At the first level of the SAT model, the operator is provided with the basic information about the agent's current state and goals, intentions, and proposed actions.…”

Section: Introductionmentioning

confidence: 99%

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Human-Autonomy Teaming and Agent Transparency

Chen

Selkowitz

Stowers

et al. 2017

Proceedings of the Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction

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We developed the user interfaces for two HRI tasking environments based on the Situation awareness-based Agent Transparency (SAT) model: dismounted infantry interacting with a ground robot (Autonomous Squad Member) and human interacting with an intelligent agent to manage a team of heterogeneous robotic vehicles (IMPACT). User testing showed that as agent transparency increased, so did human operator performance and trust calibration effectiveness. The expanded SAT model, which includes Teamwork Transparency, is also briefly described.

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Situation awareness-based agent transparency for human-autonomy teaming effectiveness

Cited by 42 publications

References 18 publications

Automation transparency: implications of uncertainty communication for human-automation interaction and interfaces

Automation transparency: implications of uncertainty communication for human-automation interaction and interfaces

Human-automation teamwork : Current practices and future directions in air traffic control

Human-Autonomy Teaming and Agent Transparency

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