Team Coordination Dynamics in Human-Autonomy Teaming

2017 ◽  
Vol 61 (1) ◽  
pp. 236-236 ◽  
Author(s):  
Mustafa Demir ◽  
Polomnia G. Amazeen ◽  
Nathan J. McNeese ◽  
Aaron Likens ◽  
Nancy J. Cooke
Keyword(s):  
Team Performance ◽  
Unmanned Aircraft ◽  
Coordination Dynamics ◽  
Team Communication ◽  
Target Level ◽  
Timely Manner ◽  
Coordination Sequence ◽  
Team Coordination ◽  
Team Members ◽  
Human Autonomy

Project overview. The current study focuses on the nature of team coordination dynamics within all-human teams and Human-Autonomy Teams (HAT) in the context of the development of a fully-fledged synthetic agent that is a computational cognitive model for a three-agent Unmanned Aircraft System (UAS) ground crew. In this study, the relationship between team coordination dynamics and team performance within the HAT and all-human teams is considered. To serve as a teammate, the synthetic agent must be able to communicate and coordinate with its human teammates in a constructive and timely manner (Demir, McNeese, & Cooke, 2016). In this current research, there were three heterogeneous team members who communicated via a text-based communication system to photograph target waypoints. Each team member had a different role: (1) navigator – provides information regarding a flight plan with speed and altitude restrictions of each waypoint; (2) pilot – controls the UAS by adjusting its altitude and airspeed by negotiating with the photographer to take a good photo for the target waypoints; and (3) photographer – screens camera settings, and sends feedback to the other team members regarding the status of target’s photograph. At each target waypoint, this coordination sequence among the team members, called Information-Negotiation-Feedback (INF), is captured by a Kappa Score (Gorman, Amazeen, & Cooke, 2010) that describes the sequence and timing of the information coordination. Three conditions were created that manipulated the pilot role: (1) Synthetic – pilot was the synthetic agent, (2) Control – pilot was a randomly assigned participant, and (3) Experimenter – pilot was an experimenter who was highly experienced with the task and focused on pushing and pulling the information in a timely manner. Method. In this experiment, there were 30 teams (ten teams for each condition): control teams were composed of three participants randomly assigned to each role; synthetic and experimenter teams were composed of only two participants randomly assigned to the navigator and photographer roles. The experiment consisted of five missions (each 40 minutes) in which teams needed to take as many “good” photos as possible of ground targets while avoiding alarms and rule violations. Several measures were obtained from this research, including team performance scores (mission and target level), team process measures (situation awareness, process ratings, communication and coordination), and other measures (teamwork knowledge, workload, and demographics). The research reported here identifies how differences in team coordination, captured by Kappa, relate to performance of all human teams and HAT teams. In this paper, we focus on: (1) target level team performance scores calculated based on the time spent inside a target waypoint to get a good photo; and (2) two team coordination dynamics measures: stability and team communication determinism. Stability was inversely related to the largest Lyapunov Exponent which was estimated by Kappa, that is, the INF coordination sequence. Team communication determinism was estimated from communication data using Joint Recurrence Quantification Analysis (Marwan, Carmen, Thiel, & Kurths, 2007) and served as an index of flexible behavior. Results and discussion. In general, findings indicate that (1) synthetic teams were most stable, followed by experimenter teams, who were moderately stable, and control teams, who were least stable; and (2) extreme stability and instability corresponded to lower levels of performance; experimenter teams performed best, followed by control teams and, then synthetic teams. Thus, synthetic agents could be made more effective if interventions were developed to enhance the flexibility and adaptive nature of HATs (Demir, 2017).

Team Situation Awareness in Human-Autonomy Teaming: A Systems Level Approach

2018 ◽  
Vol 62 (1) ◽  
pp. 149-149 ◽  
Author(s):  
David A. Grimm ◽  
Mustafa Demir ◽  
Jamie C. Gorman ◽  
Nancy J. Cooke
Keyword(s):  
Team Performance ◽  
Situation Awareness ◽  
Information Entropy ◽  
Timely Manner ◽  
Team Members ◽  
Dynamic Task ◽  
Remotely Piloted Aircraft ◽  
Human Autonomy ◽  
Team Situation Awareness ◽  
Communication Control

Project overview. The current study focuses on analyzing team flexibility by measuring entropy (where higher values correspond to system reorganization and lower values correspond to more stable system organization) across all-human teams and Human-Autonomy Teams (HAT). We analyzed teams in the context of a fully-fledged synthetic agent that acts as a pilot for a three-agent Remotely Piloted Aircraft System (RPAS) ground crew. The synthetic agent must be able to communicate and coordinate with human teammates in a constructive and timely manner to be effective. This study involved three heterogeneous team members who had to take photographs of target waypoints and communicate via a text-based communication system. The three team members’ roles were: 1) navigator provides information about flight plan with speed and altitude restrictions at each waypoint; 2) pilot adjusts altitude and airspeed to control the Remotely Piloted Aircraft (RPA), and negotiates with the photographer about the current altitude and airspeed to take good photos for the targets; and 3) photographer screens camera settings, and sends feedback to other team members regarding the target photograph status. The three conditions differed based on the manipulation of the pilot role: 1) Synthetic – the pilot was the synthetic agent, 2) Control – the pilot was a randomly assigned participant, and 3) Experimenter – the pilot was a well-trained experimenter who focused on sending and receiving information in a timely manner. The goal of this study is to examine how overall RPAS flexibility across HATs and all-human teams are associated with Team Situation Awareness (TSA). Method. There were 30 teams (10-teams per condition): control teams consisted of three participants randomly assigned to each role; synthetic and experimenter teams included two participants randomly assigned to the navigator and photographer roles. The experiment took place over five 40-minute missions, and the goal was to take as many “good” photos of ground targets as possible while avoiding alarms and rule violations. We obtained several measures, including mission and target level team performance scores, team process measures (situation awareness, process ratings, communication and coordination), and other measures (teamwork knowledge, workload, and demographics). We first estimated amount of system reorganization of the RPAS via an information entropy measure, i.e., the number of arrangements the system occupied over a given period of time (Shannon & Weaver, 1975). Based on information entropy, we defined four layers to represent the RPAS (Gorman, Demir, Cooke, & Grimm, In Review): 1) communications - the chat-based communication among team members; 2) vehicle - the RPA itself, e.g., speed, altitude; 3) control - interface between the RPA and the user; and system - the overall activity of the sub-layers. Then, we looked at the relationship between layers and TSA, which was based on successfully overcoming and completing ad hoc embedded target waypoints. Results and conclusion. Overall, the experimenter teams adapted to more roadblocks than the synthetic teams, who were equivalent to control teams (Demir, McNeese, & Cooke, 2016). The findings indicate that: 1) synthetic teams demonstrated rigid systems level activity, which consisted of less reorganization of communication, control and vehicle layers as conditions changed, which also resulted in less adaptation to roadblocks; 2) control teams demonstrated less communication reorganization, but more control and vehicle reorganization, which also resulted in less adaptation to roadblocks; and 3) experimenter teams demonstrated more reorganization across communication, control and vehicle layers, which resulted in better adaptation to roadblocks. Thus, the ability of a system to reorganize across human and technical layers as situations change is needed to adapt to novel conditions of team performance in a dynamic task

scholarly journals Layered Dynamics and System Effectiveness of Human-Autonomy Teams Under Degraded Conditions

2019 ◽  
Vol 63 (1) ◽  
pp. 165-165
Author(s):  
David A. Grimm ◽  
Mustafa Demir ◽  
Jamie C. Gorman ◽  
Nancy J. Cooke ◽  
Nathan J. McNeese
Keyword(s):  
Team Performance ◽  
Positive Association ◽  
Cyber Attacks ◽  
Coordination Dynamics ◽  
Abnormal Behavior ◽  
Autonomous Agent ◽  
Team Members ◽  
Empirical Modelling ◽  
Sociotechnical System ◽  
Human Autonomy

Project overview Teamwork can be defined as dynamic team interaction between two or more interdependent members to achieve a shared goal. Many studies have examined how coordination dynamics are associated with team effectiveness in the context of all-human teams (Gorman, Amazeen, & Cooke, 2010), and later, in human-autonomy teams (HAT)s (Demir, Likens, Cooke, Amazeen, & McNeese, 2018). HATs must have autonomous agents that act as effective teammates and help enable HATs to function as collaborative systems. Synergistic relationships among a system’s human and technological components provide the basis for emergent systems-level outcomes. Layered dynamics, a recent empirical modelling technique aimed at achieving this objective (Gorman et al., 2019), considers reorganization of the sociotechnical system across individual components and the overall system. The current study examined layered dynamics of HATs during automation and autonomy failures and addresses how members of HATs interact with each other and technological aspects of the system. Design and Method We utilized a simulated Remotely Piloted Aircrtaft System (RPAS) Synthetic Task Environment with three heteregeneous and interdepedent roles: (1) a navigator, who created a dynamic flight plan and provided waypoint related information; (2) a pilot, who used this information to monitor and adjust settings. The pilot also communicated with the photographer to negotiate settings and enable proper conditions to obtain a good photograph; and (3) a photographer, who monitored and adjusted the camera to take good target photos, and provided feedback to the team. This study utilized a Wizard of Oz paradigm, in which the navigator and photographer were instructed that the pilot was a synthetic agent. However, the pilot was a highly-trained experimenter, in a separate room, who simulated an autonomous agent using limited vocabulary. There were 22 teams, and two participants were randomly assigned to the navigator and photographer roles. This task was comprised of ten 40-minute missions, and teams needed to take as many good photos as possible while avoiding alarms and rule violations. The primary manipulation was the application of three degraded conditions: (1) automation failure - role-level display failures, (2) autonomy failure - autonomous agent’s abnormal behavior, and (3) malicious cyber-attacks - the hijaking of the RPAS, with the synthetic agent providing false, detrimental information. We symbolically represented RPAS using layered dynamics, and calculated entropy measures for each (Gorman et al., 2019): (1) communications: team members interacting within the chat system; (2) vehicle: states of the RPA, including airspeed/altitude, turns, fuel, battery, remaining film, and termperature level; and (3) controls: the interface controls between the RPA and the team members. To measure team performance, we used a time and coordination based metric for each target in each mission. Results and Discussion Our main findings were: 1) vehicle and communication entropy were higher than control entropy and were associated with better adaptation to both failures, and 2) control entropy had a negative association with initial status on team performance, while vehicle entropy had a positive association. These findings describe the tendency of low performing teams to anticipate targets poorly. This was due to a failure to interact with the technology in a timely manner. This lagged effect can be attributed to teams taking too long to interact with the technology. These findings shed light on how the layered dynamics approach can help understand team behavior under degraded conditions. Acknowledgements This research is supported by ONR Award N000141712382 (Program Managers: Marc Steinberg, Micah Clark). We also acknowledge the assistance of Steven M. Shope, Sandia Research Corporation who integrated the synthetic agent and the testbed.

The Synthetic Teammate as a Team Player in Command-and-Control Teams

2016 ◽  
Vol 60 (1) ◽  
pp. 116-116 ◽  
Author(s):  
Mustafa Demir ◽  
Nathan J. McNeese ◽  
Nancy J. Cooke ◽  
Christopher Myers
Keyword(s):  
Team Performance ◽  
Cognitive Model ◽  
Unmanned Aircraft ◽  
Recent Effort ◽  
Interaction Patterns ◽  
Team Process ◽  
Processing Efficiency ◽  
Specific Sequence ◽  
Team Members ◽  
Team Player

Project overview. The current project is part of a larger effort that focuses on Human-Automation Teaming (HAT) interaction in the context of the development, integration, and validation of a computational cognitive model that acts as a full-fledged synthetic teammate for a three-agent Unmanned Aircraft System (UAS) ground control crew. Our most recent effort looked at team process and team performance within the HAT. In order to be considered a team player, the synthetic teammate must be able to communicate and coordinate with its human teammates and do so in a subtle manner (Demir et al., 2016). In this task, there were three different and interdependent team members: 1) Air Vehicle Operator (AVO) – controls the UAS’s heading, altitude, and airspeed; 2) Data Exploitation, Mission Planning, and Communications (DEMPC) – provides a dynamic flight plan as well as speed and altitude restrictions; and 3) Payload Operator (PLO) – monitors sensor equipment, negotiates with the AVO, and takes photographs of target waypoints. The communication within a three-agent UAS team occurred over a text-based communications system. In this research, there were three conditions which are differentiated by the AVO role: 1) the Synthetic - the synthetic teammate was assigned the AVO role; 2) the Control - the AVO was an inexperienced human participant; 3) the Experimenter - the AVO was one of the experimenters who was experienced with the task. The experimenter AVO asked questions of other team members to ensure timely and adaptive passing of information at target waypoints. In this current study, the coordination among the team members occurs at each target waypoint and requires a specific sequence of information passing for an optimum team performance (Cooke, Gorman, Duran, & Taylor, 2007): the information is provided by the DEMPC about the upcoming target waypoint to the AVO. After that, the PLO and the AVO negotiate regarding an appropriate altitude and airspeed for the target waypoints about required camera settings. Finally, the PLO sends feedback to other team members about the status of the target photo. Method. Activities during this period included conducting an experiment to: 1) evaluate the synthetic teammate’s performance, and the HAT team performance in comparison to all human teams, 2) understand how team process differs between all human and human-synthetic teams and how this impacts performance, and 3) compare the human-synthetic teams and all human control teams to a team with a pilot that is experienced in pushing and pulling information across the team. For this experiment, participants were randomly assigned for the duration of the experiment. Within each of the five missions, teams were told to obtain as many “good” photos as possible while avoiding alarms and rule violations in less than 40 minutes. The overall focus of this paper is: team process that is comprised of eight verbal behaviors associated with team effectiveness; team performance that is a combination of mission variables, including the rate of successful target photographs, time spent in alarm and warning states (for each individual), and the critical waypoint acquisition rate; and target processing efficiency took into account the time spent inside a target waypoint to get a good photo. Results and discussion. In general, findings indicate that synthetic AVOs perform more poorly than control AVOs in terms of team performance. Synthetic teams perform as well at the mission level as control teams. However, in terms of target processing efficiency, synthetic teams perform poorer than control teams. In terms of team process, synthetic teams demonstrate interaction patterns corresponding to more pulling of information than pushing with little change over time. In summary, these results indicate that there is a strong potential for using synthetic team member as a teammate in real world tasks and for training.

Is the Most Effective Team Leadership Shared?

2010 ◽  
Vol 9 (3) ◽  
pp. 105-116 ◽  
Author(s):  
Julia Elisabeth Hoch ◽  
Craig L. Pearce ◽  
Linda Welzel
Keyword(s):  
Team Performance ◽  
Shared Leadership ◽  
Team Leadership ◽  
Project Teams ◽  
Team Coordination ◽  
Team Members ◽  
Age Diversity ◽  
Performance Results ◽  
The Impact ◽  
The Relationship

In the present paper we examine the moderating effects of age diversity and team coordination on the relationship between shared leadership and team performance. Using a field sample of 96 individuals in 26 consulting project teams, team members assessed their team’s shared leadership and coordination. Six to eight weeks later, supervisors rated their teams’ performance. Results indicated that shared leadership predicted team performance and both age diversity and coordination moderated the impact of shared leadership on team performance. Thereby shared leadership was positively related to team performance when age diversity and coordination were low, whereas higher levels of age diversity and coordination appeared to compensate for lower levels of shared leadership effectiveness. In particular strong effects of shared leadership on team performance were evident when both age diversity and coordination were low, whereas shared leadership was not related to team performance when both age diversity and coordination were high.

scholarly journals Approaches for assessing communication in human-autonomy teams

2021 ◽  
Author(s):  
Anthony L. Baker ◽  
Sean M. Fitzhugh ◽  
Lixiao Huang ◽  
Daniel E. Forster ◽  
Angelique Scharine ◽  
...  
Keyword(s):  
Performance Outcomes ◽  
Lessons Learned ◽  
Future Research ◽  
Emotional States ◽  
Team Communication ◽  
Military Operations ◽  
Team Members ◽  
Team Interactions ◽  
Human Autonomy ◽  
And Performance

AbstractEvaluation of team communication can provide critical insights into team dynamics, cohesion, trust, and performance on joint tasks. Although many communication-based measures have been tested and validated for human teams, this review article extends this research by identifying key approaches specific to human-autonomy teams. It is not possible to identify all approaches for all situations, though the following seem to generalize and support multi-size teams and a variety of military operations. Therefore, this article will outline several key approaches to assessing communication, associated data requirements, example applications, verification of methods through HAT use cases, and lessons learned, where applicable. Some approaches are based on the structure of team communication; others draw from dynamical systems theory to consider perspectives across different timescales; other approaches leverage features of team members’ voices or facial expressions to detect emotional states that can provide windows into other workings of the team; still others consider the content of communication to produce insights. Taken together, these approaches comprise a varied toolkit for deriving critical information about how team interactions affect, and are affected by, coordination, trust, cohesion, and performance outcomes. Future research directions describe four critical areas for further study of communication in human-autonomy teams.

Development of a German-Language Questionnaire to Measure Collective Orientation as an Individual Attitude

2017 ◽  
Vol 76 (3) ◽  
pp. 91-105 ◽  
Author(s):  
Vera Hagemann
Keyword(s):  
Team Performance ◽  
Reliability And Validity ◽  
Future Research ◽  
German Language ◽  
Team Members ◽  
Collective Orientation ◽  
Team Research ◽  
German Speaking ◽  
Individual Variables ◽  
The Individual

Abstract. The individual attitudes of every single team member are important for team performance. Studies show that each team member’s collective orientation – that is, propensity to work in a collective manner in team settings – enhances the team’s interdependent teamwork. In the German-speaking countries, there was previously no instrument to measure collective orientation. So, I developed and validated a German-language instrument to measure collective orientation. In three studies (N = 1028), I tested the validity of the instrument in terms of its internal structure and relationships with other variables. The results confirm the reliability and validity of the instrument. The instrument also predicts team performance in terms of interdependent teamwork. I discuss differences in established individual variables in team research and the role of collective orientation in teams. In future research, the instrument can be applied to diagnose teamwork deficiencies and evaluate interventions for developing team members’ collective orientation.

Is the bottom line reached? An exploration of supervisor bottom-line mentality, team performance avoidance goal orientation and team performance

2021 ◽  
pp. 001872672110029
Author(s):  
Yuying Lin ◽  
Mengxi Yang ◽  
Matthew J Quade ◽  
Wansi Chen
Keyword(s):  
Goal Orientation ◽  
Team Performance ◽  
Social Information Processing ◽  
Negative Relationship ◽  
Bottom Line ◽  
Team Members ◽  
Processing Theory ◽  
Using Data ◽  
Exclusive Focus ◽  
Avoidance Goal

How do supervisors who treat the bottom line as more important than anything else influence team success? Drawing from social information processing theory, we explore how and when supervisor bottom-line mentality (i.e. an exclusive focus on bottom-line outcomes at the expense of other priorities) exerts influence on the bottom-line itself, in the form of team performance. We argue that a supervisor’s bottom-line mentality provides significant social cues for the team that securing bottom-line objectives is of sole importance, which stimulates team performance avoidance goal orientation, and thus decreases team performance. Further, we argue performing tension (i.e. tension between contradictory needs, demands, and goals), serving as team members’ mutual perception of the confusing environment, will strengthen the indirect negative relationship between supervisor bottom-line mentality and team performance through team performance avoidance goal orientation. We conduct a path analysis using data from 258 teams in a Chinese food-chain company, which provides support for our hypotheses. Overall, our findings suggest that supervisor’s exclusive focus on the bottom-line can serve to impede team performance. Theoretical contributions and practical implications are discussed.

Trust and Team Performance in Human–Autonomy Teaming

2021 ◽  
Vol 25 (1) ◽  
pp. 51-72
Author(s):  
Nathan J. McNeese ◽  
Mustafa Demir ◽  
Erin K. Chiou ◽  
Nancy J. Cooke
Keyword(s):  
Team Performance ◽  
Human Autonomy

Development of Team Coordination and Performance Measures in a Trauma Setting

2007 ◽  
Vol 51 (11) ◽  
pp. 717-721 ◽  
Author(s):  
Stuart Marshall ◽  
Anne Miller ◽  
Yan Xiao
Keyword(s):  
Team Performance ◽  
Decision Support Tool ◽  
Stage Model ◽  
Trauma Resuscitation ◽  
Team Coordination ◽  
Support Tool ◽  
University Of Maryland ◽  
Performance Metric ◽  
And Performance ◽  
The University

The paucity of reliable measures of team coordination and performance significantly obstructs the assessment of the effects of any technology on teams to improve decision making in health care. A pilot study was conducted to determine if measures of coordination and performance could be developed for teams involved in trauma resuscitation. A video assisted review of cases enabled evaluation of the use of the tools. Descriptors of coordination were derived from Klein's five-stage model of team coordination. A scoring system of team performance was developed from the University of Maryland Team Observable Performance Metric (UMTOP). After some modification both coordination and performance could be described. However, four defined stages of resuscitation were observed which greatly improved coding. More rigorous assessments of these tools will be required before firm conclusions can be drawn about the effects of a decision support tool recently introduced into the environment.

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