A User Study Evaluation of Predictive Formal Modelling at Runtime in Human-Swarm Interaction

Formal Modelling is often used as part of the design and testing process of software development to ensure that components operate within suitable bounds even in unexpected circumstances. We conducted a user study evaluation of predictive formal modelling (PFM) at runtime in a human-swarm mission to determine the benefit of PFM on performance and human-swarm interaction. A total of 180 participants were recruited to perform the role of aerial swarm operators delivering parcels to target locations in a simulation environment. The PFM model was integrated into the simulation software to inform the operator of the estimated mission completion time given the current number of drones deployed. The operator could increase the number of parcels delivered in any timestep by adding drones, which also increased costs, thus requiring the use of the minimum number of drones necessary to complete the task in the given time. We collected user feedback using standard survey questionnaires and measured performance using data obtained from the Human and Robot Interactive Swarm (HARIS) simulator. Our results show that PFM increased the performance of the human swarm team without significantly increasing the operators’ workload or affecting the system’s usability.

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Publication Details

Journal
ACM Transactions on Human-Robot Interaction
Published
2025-04-04
DOI
https://doi.org/10.1145/3727989
Primary Topic
Semantic Web and Ontologies
Type
article
Field-Weighted Citation Impact
0.00

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article

A User Study Evaluation of Predictive Formal Modelling at Runtime in Human-Swarm Interaction

Blair Archibald, Eike Schneiders, Michele Sevegnani, Ayodeji O. Abioye et al.
ACM Transactions on Human-Robot Interaction
Semantic Web and Ontologies
article

A User Study Evaluation of Predictive Formal Modelling at Runtime in Human-Swarm Interaction

Blair Archibald, Eike Schneiders, Michele Sevegnani, Ayodeji O. Abioye, Sarvapali D. Ramchurn, Mohammad Naiseh, Mohammad Divband Soorati, Joel E. Fischer, Yue Gu, William Hunt
article en

Abstract

Formal Modelling is often used as part of the design and testing process of software development to ensure that components operate within suitable bounds even in unexpected circumstances. We conducted a user study evaluation of predictive formal modelling (PFM) at runtime in a human-swarm mission to determine the benefit of PFM on performance and human-swarm interaction. A total of 180 participants were recruited to perform the role of aerial swarm operators delivering parcels to target locations in a simulation environment. The PFM model was integrated into the simulation software to inform the operator of the estimated mission completion time given the current number of drones deployed. The operator could increase the number of parcels delivered in any timestep by adding drones, which also increased costs, thus requiring the use of the minimum number of drones necessary to complete the task in the given time. We collected user feedback using standard survey questionnaires and measured performance using data obtained from the Human and Robot Interactive Swarm (HARIS) simulator. Our results show that PFM increased the performance of the human swarm team without significantly increasing the operators’ workload or affecting the system’s usability.

ACM Transactions on Human-Robot InteractionVol. 14(4)
University of Nottingham (GB), The Open University (GB), University of Southampton (GB), University of Glasgow (GB), Bournemouth University (GB)
UK Research and Innovation, Engineering and Physical Sciences Research Council
Openalex Percentile: Top 97%
Semantic Web and Ontologies
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