A visualization tool of en route air traffic control tasks for describing controller’s proactive management of traffic situations

Karikawa, Daisuke; Aoyama, Hisae; Takahashi, Makoto; Furuta, K.; Wakabayashi, Toshio; Kitamura, M.

doi:10.1007/s10111-012-0222-y

Cited by 9 publications

(5 citation statements)

References 8 publications

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“…Past work has shown that an agent's reliability and its task performance heavily influences users' disposition to trust it [19,37]. In HAC scenarios, agents are generally introduced to reduce users' cognitive workload, while trying to improve users' situational awareness and overall task performance [10,13,25,41].…”

Section: Performance and Reliabilitymentioning

confidence: 99%

Impact of Agent Reliability and Predictability on Trust in Real Time Human-Agent Collaboration

Daronnat

Azzopardi

Halvey

et al. 2020

Proceedings of the 8th International Conference on Human-Agent Interaction

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Trust is a prerequisite for effective human-agent collaboration. While past work has studied how trust relates to an agent's reliability, it has been mainly carried out in turn based scenarios, rather than during real-time ones. Previous research identified the performance of an agent as a key factor influencing trust. In this work, we posit that an agent's predictability also plays an important role in the trust relationship, which may be observed based on users' interactions. We designed a 2x2 within-groups experiment with two baseline conditions: (1) no agent (users' individual performance), and (2) near-flawless agent (upper bound). Participants took part in an interactive aiming task where they had to collaborate with different agents that varied in terms of their predictability, and were controlled in terms of their performance. Our results show that agents whose behaviours are easier to predict have a more positive impact on task performance, reliance and trust while reducing cognitive workload. In addition, we modelled the human-agent trust relationship and demonstrated that it is possible to reliably predict users' trust ratings using real-time interaction data. This work seeks to pave the way for the development of trust-aware agents capable of adapting and responding more appropriately to users. CCS CONCEPTS • Human-centered computing → Empirical studies in HCI; Collaborative interaction; User studies; Laboratory experiments.

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Section: Performance and Reliabilitymentioning

confidence: 99%

Impact of Agent Reliability and Predictability on Trust in Real Time Human-Agent Collaboration

Daronnat

Azzopardi

Halvey

et al. 2020

Proceedings of the 8th International Conference on Human-Agent Interaction

View full text Add to dashboard Cite

show abstract

“…A comprehensive review by Honig and Oron-Gilad (2018) highlights past research focusing on agents' failures and their impacts on users. In HAC scenarios, agents are generally introduced to reduce users' cognitive workload, while trying to improve users' situational awareness and overall task performance (Stowers et al, 2017;Demir et al, 2017;Karikawa et al, 2013;Fan et al, 2010). Fan et al (2008) tested different levels of agents' variability (using systematic biases) in a turn-based Command and Control threat assessment task.…”

Section: Performance and Reliabilitymentioning

confidence: 99%

Inferring Trust From Users’ Behaviours; Agents’ Predictability Positively Affects Trust, Task Performance and Cognitive Load in Human-Agent Real-Time Collaboration

et al. 2021

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Collaborative virtual agents help human operators to perform tasks in real-time. For this collaboration to be effective, human operators must appropriately trust the agent(s) they are interacting with. Multiple factors influence trust, such as the context of interaction, prior experiences with automated systems and the quality of the help offered by agents in terms of its transparency and performance. Most of the literature on trust in automation identified the performance of the agent as a key factor influencing trust. However, other work has shown that the behavior of the agent, type of the agent’s errors, and predictability of the agent’s actions can influence the likelihood of the user’s reliance on the agent and efficiency of tasks completion. Our work focuses on how agents’ predictability affects cognitive load, performance and users’ trust in a real-time human-agent collaborative task. We used an interactive aiming task where participants had to collaborate with different agents that varied in terms of their predictability and performance. This setup uses behavioral information (such as task performance and reliance on the agent) as well as standardized survey instruments to estimate participants’ reported trust in the agent, cognitive load and perception of task difficulty. Thirty participants took part in our lab-based study. Our results showed that agents with more predictable behaviors have a more positive impact on task performance, reliance and trust while reducing cognitive workload. In addition, we investigated the human-agent trust relationship by creating models that could predict participants’ trust ratings using interaction data. We found that we could reliably estimate participants’ reported trust in the agents using information related to performance, task difficulty and reliance. This study provides insights on behavioral factors that are the most meaningful to anticipate complacent or distrusting attitudes toward automation. With this work, we seek to pave the way for the development of trust-aware agents capable of responding more appropriately to users by being able to monitor components of the human-agent relationships that are the most salient for trust calibration.

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“…Cognitive strategies of ATCOs in real work situations were explored by Karikawa et al (2013) and visualization tools of en-route tasks were developed to analyze the performance of controllers' strategies (Karikawa et al, 2014). More recently, Edwards et al (2017) studied the interaction of situation awareness and workload for different levels of automation in a real environment as well.…”

Section: Atcos' Cognitive Processesmentioning

confidence: 99%

Understanding and overcoming horizontal separation complexity in air traffic control: an expert/novice comparison

et al. 2020

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Humans still play a key role in air traffic control but their performances limit the capacity of the airspace and are responsible for delays. At the tactical level, even though Air Traffic Controllers (ATCO) are trained for years, their performances are limited. In this article, we first isolated the tactical horizontal deconfliction task and explained its mathematical complexity. We observed through a simple experiment conducted on

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A visualization tool of en route air traffic control tasks for describing controller’s proactive management of traffic situations

Cited by 9 publications

References 8 publications

Impact of Agent Reliability and Predictability on Trust in Real Time Human-Agent Collaboration

Impact of Agent Reliability and Predictability on Trust in Real Time Human-Agent Collaboration

Inferring Trust From Users’ Behaviours; Agents’ Predictability Positively Affects Trust, Task Performance and Cognitive Load in Human-Agent Real-Time Collaboration

Understanding and overcoming horizontal separation complexity in air traffic control: an expert/novice comparison

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