Bidirectional Communications in Human-Agent Teaming: The Effects of Communication Style and Feedback

Abstract

We examined the effects of communication style on human performance, workload, situation awareness, and trust in a robot in a human-robot team. In a 2 × 2 mixed factor study, participants were teamed with a simulated robot to conduct a cordon-and-search style task. Participants were assigned to a communication style (Directive vs. Non-directive; between subjects), and both groups experienced varied periods of task load (high vs. low task load; within-subjects). Results indicate that task load influenced the participants' task performance more than communication style. However, there were some differential effects on response time and workload due to communication style. Participants in the Non-directive group did not report a higher workload than those in the Directive condition, even though objective measures of workload (i.e., eye-tracking measures) indicated they experienced a higher workload. These results may be due to the presence of feedback inherent in the differing communication styles.

Acknowledgments

We would like to thank Jonathan Coole, Justin Lee, and Jacquelyn Schreck for their efforts in supporting this study.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Julia L. Wright

Julia L. Wright, is a Research Psychologist with U.S. Army Research Laboratory—Human Research and Engineering Directorate in Orlando, Florida. Her research interest is how to bridge the intuitive gap between humans and technology, which includes examining human performance in human-autonomy teaming, human-technology interaction, and agent transparency.

Shan G. Lakhmani

Shan G. Lakhmani, is a research psychologist with US Army Research Laboratory-Human Research and Engineering Directorate in Orlando, Florida. His research interests include group dynamics in human-autonomy teams, transparent human-autonomy interaction, and using technology to help build understanding in complex environments.

Jessie Y. C. Chen

Jessie Y. C. Chen is a Senior Research Scientist (ST) for Soldier Performance in Socio-Technical Systems with U.S. Army Research Laboratory, located in Aberdeen Proving Ground, MD. Her research interests include human-autonomy teaming, agent transparency, human-robot interaction, and human supervisory control.