The Effect of Data Visualisation Quality and Task Density on Human-Swarm Interaction
Ayodeji O. Abioye, Mohammad Naiseh, William Hunt, Jediah Clark,, Sarvapali D. Ramchurn, and Mohammad D. Soorati

TL;DR
This study investigates how data quality affects human-swarm interaction, showing that high-quality data increases workload and trust but does not significantly improve task success rates in casualty identification.
Contribution
It provides empirical evidence on the impact of data visualisation quality on human trust, workload, and task performance in human-swarm systems.
Findings
High-quality data increases human trust and workload.
Task success rate is unaffected by data quality.
Participants with high-quality data identified casualties equally well.
Abstract
Despite the advantages of having robot swarms, human supervision is required for real-world applications. The performance of the human-swarm system depends on several factors including the data availability for the human operators. In this paper, we study the human factors aspect of the human-swarm interaction and investigate how having access to high-quality data can affect the performance of the human-swarm system - the number of tasks completed and the human trust level in operation. We designed an experiment where a human operator is tasked to operate a swarm to identify casualties in an area within a given time period. One group of operators had the option to request high-quality pictures while the other group had to base their decision on the available low-quality images. We performed a user study with 120 participants and recorded their success rate (directly logged via the…
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Taxonomy
TopicsHuman-Automation Interaction and Safety · Virtual Reality Applications and Impacts · Mobile Crowdsensing and Crowdsourcing
