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Where Do You Think You're Going?: Characterizing Spatial Mental Models from Planned Routes

Authors:

Brandon S. Perelman,

Arthur W. Evans III,

Kristin E. SchaeferAuthors Info & Claims

ACM Transactions on Human-Robot Interaction (THRI), Volume 9, Issue 4

Article No.: 23, Pages 1 - 55

https://doi.org/10.1145/3385008

Published: 31 May 2020 Publication History

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Abstract

Route planning is a critical behavior for human-intelligent agent (H-IA) team mobility. The scientific community has made major advances in improving route planner optimality and speed. However, human factors, such as the ability to predict and understand teammates’ actions and goals, are necessary for trust development in H-IA teams. Trust is especially critical when agents’ behaviors do not match human team members’ expectations, or the human cannot understand the agent's underlying reasoning process. To address this issue, the artificial intelligence community has pushed toward creating human-like agent behaviors using machine learning. The problem with this approach is that we do not yet have a clear understanding of what constitutes human-like behavior across the breadth of tasks that H-IA teams undertake. This article describes an investigation and comparison of human and agent route planning behaviors, the interplay between humans and agents in collaborative planning, and the role of trust in this collaborative process. Finally, we propose a data-driven methodology for characterizing and visualizing differences among routes planned by humans and agents. This methodology provides a means to advance compatible mental model metrics and theory by informing targeted transparency manipulations, thereby improving the speed and quality of routes produced by H-IA teams.

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cover image ACM Transactions on Human-Robot Interaction

ACM Transactions on Human-Robot Interaction Volume 9, Issue 4

December 2020

192 pages

EISSN:2573-9522

DOI:10.1145/3403615

Editors:
Odest Chadwicke Jenkins
University of Michigan, USA
,
Selma Sabanovic
Indiana University, USA

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Publication History

Published: 31 May 2020

Online AM: 07 May 2020

Accepted: 01 February 2020

Revised: 01 November 2019

Received: 01 March 2019

Published in THRI Volume 9, Issue 4

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Cited By

Smith DManzini DKennedy DIves P(2023)Ethics of Trust/worthiness in Autonomous Systems: a scoping review.Proceedings of the First International Symposium on Trustworthy Autonomous Systems10.1145/3597512.3600207(1-15)Online publication date: 11-Jul-2023
https://dl.acm.org/doi/10.1145/3597512.3600207
Deniz NOzceylan E(2022)A bibliometric and social network analysis of data-driven heuristic methods for logistics problemsJournal of Industrial and Management Optimization10.3934/jimo.2022190(0)Online publication date: 2022
https://doi.org/10.3934/jimo.2022190
Lin JPanganiban AMatthews GGibbins KAnkeney ESee CBailey RLong M(2022)Trust in the Danger Zone: Individual Differences in Confidence in Robot Threat AssessmentsFrontiers in Psychology10.3389/fpsyg.2022.60152313Online publication date: 31-Mar-2022
https://doi.org/10.3389/fpsyg.2022.601523
Krausman ANeubauer CForster DLakhmani SBaker AFitzhugh SGremillion GWright JMetcalfe JSchaefer K(2022)Trust Measurement in Human-Autonomy Teams: Development of a Conceptual ToolkitACM Transactions on Human-Robot Interaction10.1145/353087411:3(1-58)Online publication date: 2-Sep-2022
https://dl.acm.org/doi/10.1145/3530874
Vereschak OBailly GCaramiaux B(2021)How to Evaluate Trust in AI-Assisted Decision Making? A Survey of Empirical MethodologiesProceedings of the ACM on Human-Computer Interaction10.1145/34760685:CSCW2(1-39)Online publication date: 18-Oct-2021
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Metcalfe JPerelman BBoothe DMcdowell K(2021)Systemic Oversimplification Limits the Potential for Human-AI PartnershipIEEE Access10.1109/ACCESS.2021.30782989(70242-70260)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3078298
Schaefer KPerelman BRexwinkle JCanady JNeubauer CWaytowich NLarkin GCox KGeuss MGremillion GMetcalfe JDeCostanza AMarathe A(2021)Human-Autonomy Teaming for the Tactical Edge: The Importance of Humans in Artificial Intelligence Research and DevelopmentSystems Engineering and Artificial Intelligence10.1007/978-3-030-77283-3_7(115-148)Online publication date: 2-Nov-2021
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