- Research:
- UAV Command-and-control
Past Empirical Efforts in the UAV Ground Control Testbed
To date, 6 experiments, all supported by the Air Force Office of Scientific
Research, have been run in the context of the UAV ground control testbed.
Past experiments have examined:
• Performance acquisition over the course of 11 40-minute missions
• The effect of shared vs. non-shared knowledge on performance
• The effects of workload and co-location (co-located vs. distributed) on performance
• For all male teams only, the effects of workload and co-location on performance
Other variables measured include:
• Situation awareness
• Teamwork knowledge
• Taskwork knowledge
• Team process
• Leadership
• Demographics
Some of the most interesting findings from past experiments are highlighted below.
FINDING: TEAMS REACH ASYMPTOTIC LEVELS OF PERFORMANCE AFTER FOUR 40-MINTUE
MISSIONS.
As illustrated in the figure below, team performance asymptotes around Mission
4 The decline in performance at Mission 8 can be attributed to the fact that
this is the first mission that occurred right after spring break, when participants
came back into the lab to complete the study.
FINDING: DIFFERENT TEAM ROLES ARE AFFECTED BY AND PERCEIVE INCREASES IN WORKLOAD DIFFERENTLY.
Different roles on the UAV team do not experience workload in the same way. When performing high workload missions, DEMPCS, the mission coordinators, perceived the largest increase in workload.
FINDING: Co-located teams exhibited better overall critical incident process behaviors.
Critical incident process behaviors tended to involve planning and adaptive process behaviors. Compared to co-located teams, distributed teams debrief less, talk less, and display a greater variety of communication flow patterns. Furthermore, at a communication glitch, co-located teams became more like distributed teams in terms of their communication. Perhaps the process differences are adaptive to the distributed environment.
FINDING: The team with the best performance in the history of the CERTT Lab was a team of 3 males who play video games over the internet, in a distributed fashion, on a daily basis.
In an experiment where 5 expert teams, in terms of their prior experience working together, performed five 40-minute missions, the top performing team was a group of 3 males who play the video game, Counter Strike, on a daily basis over the internet. Their team performance is represented by the royal blue line in the figure below. Notice how their performance in Mission 1 was typical, likely due to their unfamiliarity with the missions; however, the team reach asymptotic performance on the second mission, where it usually takes teams 4 missions to do the same. The red line in the figure below represents the performance of a team of CERTT Lab experimenters. Due to their familiarity with the task, their performance was very high from the start.
Current Empirical & Modeling Efforts in the UAV Ground Control Testbed
In current efforts, supported by the Air Force Office of Scientific Research, the CERTT Lab is empirically studying and modeling the acquisition and retention of command-and control coordination. This effort consist of 4 main objectives:
OBJECTIVE 1: Derive a local optimal model and metric for team coordination in the context of the UAV-STE.
Optimal coordination will be modeled in order to 1) establish a benchmark that reflects ideal coordination so that conclusions can be drawn about the degree to which training or other interventions are effective, 2) provide a coordination metric that can be used to inform the development of models of coordination acquisition and retention( Objective 3), and 3) offer a more continuous metric of team performance within a mission (as opposed to a single mission outcome).
The figure bellows illustrates the idea of comparing each
team’s coordination to some optimum and generating a score based on
how closely the observed coordination and the optimum align.
OBJECTIVE 2: Identify empirical acquisition and retention functions for team coordination
The CERTT Lab would like to withhold specific information about this effort until the experiment has been completed. Please contact ncooke@asu.edu if you would like more information.
OBJECTIVE 3: Model development of team coordination in command-and-control
using dynamical systems approach
A dynamical systems approach will be used to model the acquisition and retention of team coordination skill. The model will ultimately suggest training interventions and will enable predictions regarding coordination retention using control parameters.
The figure below
illustrates, in general, the idea of a dynamic system.
OBJECTIVE 4: Collect additional data to test model predictions regarding interventions to improve retention
In order to make recommendations for the improved retention of team coordination skill, an experiment will be designed to test the model predictions generated by Objective 3. The experiment will take place in the UAV testbed.
Cognitive Task Analysis of a Deployable UAV Operations Cell
The CERTT Lab recently worked in collaboration with US Positioning on a Phase I SBIR contract supported by the Air Force Research Laboratory at Wright Patterson AFB that was aimed at guiding the design of a Deployable UAV Operations Cell (DUOC). Human effectiveness methodologies and procedures, such as a cognitive task analysis, were used to assess and improve the DUOC team structure, information displays, communications, and information sharing. The DUOC is an initiative of the UAV Battlelab, Indian Springs AFB and it will be an important element in the overall command and control of UAVs, which are becoming and increasingly important military asset.
For more information, visit http://www.uspositioning.com/info_sys/duoc.shtml
UAV Workshop & Book on Human Factors of Remotely Piloted Vehicles
The first Human Factors of UAVs workshop was hosted by the Cognitive Engineering Research Institute (CERI) in May 2004. Critical issues relevant to human factors and UAVs were identified by UAV operators, researchers and developers. A book will be assembled to document the issues identified and will include many of the specific projects that were presented at the workshop.
Nancy J. Cooke, CERI/ Arizona State University East
Heather Pringle, Air Force Research Laboratory, Mesa AZ
Harry Pedersen, CERI/ New Mexico State University
Olena Connor, CERI/ New Mexico State University
Human Factors of Remotely Piloted Vehicles will be published in a future volume in Advances in Human Performance and Cognitive Engineering Research Series (Series Editor: Eduardo Salas, University of Central Florida).
To
read more about the workshop or the book, visit the CERI
website.
