Exploration of Teammate Trust and Interaction Dynamics in Human-Autonomy Teaming

Mustafa Demir, Nathan J. McNeese, Jaime C. Gorman, Nancy J. Cooke, Christopher W. Myers, David A. Grimm

Research output: Contribution to journalArticlepeer-review

24 Scopus citations


This article considers human-autonomy teams (HATs) in which two human team members interact and collaborate with an autonomous teammate to achieve a common task while dealing with unexpected technological failures that were imposed either in automation or autonomy. A Wizard of Oz methodology is used to simulate the autonomous teammate. One of the critical aspects of HAT performance is the trust that develops over time as team members interact with each other in a dynamic task environment. For this reason, it is important to examine the dynamic nature of teammate trust through real-time measures of team interactions. This article examines team interaction and trust to understand better how they change under automation and autonomy failures. Thus, we address two research questions: 1) How does trust in HATs evolve over time?; and 2) How is the relationship between team interaction and trust impacted by the failures? We hypothesize that trust in HATs will decrease as autonomy failures increase. We also hypothesize that team interaction would be related to the development of trust and recovery from the failures. The results implicate three general trends: 1) team interaction dynamics are linked to the development of trust in HATs; 2) trust in the autonomous teammate is only associated with recovery from autonomy failures; 3) team interaction dynamics are related to both automation and autonomy failure recovery.

Original languageEnglish (US)
Pages (from-to)696-705
Number of pages10
JournalIEEE Transactions on Human-Machine Systems
Issue number6
StatePublished - Dec 1 2021


  • Artificial intelligence
  • dynamical systems
  • team coordination
  • trust
  • unmanned air vehicle systems

ASJC Scopus subject areas

  • Human Factors and Ergonomics
  • Control and Systems Engineering
  • Signal Processing
  • Human-Computer Interaction
  • Computer Science Applications
  • Computer Networks and Communications
  • Artificial Intelligence


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