Approved for public release; distribution is unlimited.ii REPORT DOCUMENTATION PAGE Form Approved OMB No. 0704-0188Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing the burden, to Department of Defense, Washington Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. REPORT DATE (DD-MM-YYYY) April 20142. REPORT TYPE PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) U.S. Army Research Laboratory ATTN: RDRL-HRM-AR Aberdeen Proving Ground, MD 21005-5425 PERFORMING ORGANIZATION REPORT NUMBER ARL-TR-6905 SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES)Office of the Secretary of Defense Autonomy Research Pilot Initiative 1400 Defense Pentagon Washington, DC 20301-1400 SPONSOR/MONITOR'S ACRONYM(S)OSD ARPI SPONSOR/MONITOR'S REPORT NUMBER(S) DISTRIBUTION/AVAILABILITY STATEMENTApproved for public release; distribution is unlimited. SUPPLEMENTARY NOTES* University of Central Florida -Institute for Simulation and Training, 3100 Technology Pkwy, Orlando, FL 32826 ABSTRACTWe have provided a model and framework as a foundation for transparent interfaces via our Situation Awareness-based Agent Transparency (SAT) model. In this report we discuss the implications of agent transparency for operator trust and workload; we also review potential user interface designs (information visualization and displaying uncertainty information) to support agent transparency. Finally, we provide examples of transparent interface design efforts currently ongoing at the U

Objective: We investigated performance, workload, and stress in groups of paired observers who performed a vigilance task in a coactive (independent) manner.Background: Previous studies have demonstrated that groups of coactive observers detect more signals in a vigilance task than observers working alone. Therefore, the use of such groups might be effective in enhancing signal detection in operational situations. However, concern over appearing less competent than one's cohort might induce elevated levels of workload and stress in coactive group members and thereby undermine group performance benefits. Accordingly, we performed the initial experiment comparing workload and stress in observers who performed a vigilance task coactively with those of observers who performed the vigilance task alone.Method: Observers monitored a video display for collision flight paths in a simulated unmanned aerial vehicle control task. Self-reports of workload and stress were secured via the NASA-Task Load Index and the Dundee Stress State Questionnaire, respectively.Results: Groups of coactive observers detected significantly more signals than did single observers. Coacting observers did not differ significantly from those operating by themselves in terms of workload but did in regard to stress; posttask distress was significantly lower for coacting than for single observers.Conclusion: Performing a visual vigilance task in a coactive manner with another observer does not elevate workload above that of observers working alone and serves to attenuate the stress associated with vigilance task performance.Application: The use of coacting observers could be an effective vehicle for enhancing performance efficiency in operational vigilance.

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Through a series of investigations involving different levels of contextual fidelity we developed scales of perceived urgency for several dimensions of the auditory, visual, and tactile modalities. Psychophysical ratings of perceived urgency, annoyance, and acceptability as well as behavioral responses to signals in each modality were obtained and analyzed using Steven's Power Law to allow comparison across modalities. Obtained results and their implications for use as in-vehicle alerts and warnings are discussed.

Previous studies have begun exploring the possibility that “adaptable” automation, in which tasks are delegated to intelligent automation by the user, can preserve the benefits of automation while minimizing its costs. One approach to adaptable automation is the Playbook®interface, which has been used in previous research and has shown performance enhancements as compared to other automation approaches. However, additional investigations are warranted to evaluate both benefits and potential costs of adaptable automation. The present study incorporated a delegation interface into a new display and simulation system, the multiple unmanned aerial vehicle simulator (MUSIM), to allow for flexible control over three unmanned aerial vehicles (UAVs) at three levels of delegation abstraction. Task load was manipulated by increasing the frequency of primary and secondary task events. Additionally, participants experienced an unanticipated event that was not a good fit for the higher levels of delegation abstraction. Treatment of this poor “automation fit” event, termed a “Non-Optimal Play Environment” event (NOPE event), required the use of manual control. Results showed advantages when access to the highest levels of delegation abstraction was provided and as long as operators also had the flexibility to revert to manual control. Performance was better across the two task load conditions and reaction time to respond to the NOPE event was fastest in this condition. The results extend previous findings showing benefits of flexible delegation of tasks to automation using the Playbook interface and suggest that Playbook remains robust even in the face of poor “automation-fit” events.