Operators currently controlling Unmanned Aerial Vehicles report significant boredom, and such systems will likely become more automated in the future. Similar problems are found in process control, commercial aviation, and medical settings. To examine the effect of boredom in such settings, a long duration low task load experiment was conducted. Three low task load levels requiring operator input every 10, 20, or 30 minutes were tested in a four-hour study using a multiple unmanned vehicle simulation environment that leverages decentralized algorithms for sometimes imperfect vehicle scheduling. Reaction times to system-generated events generally decreased across the four hours, as did participants' ability to maintain directed attention. Overall, participants spent almost half of the time in a distracted state. The top performer spent the majority of time in directed and divided attention states.Unexpectedly, the second-best participant, only 1% worse than the top performer, was distracted almost one third of the experiment, but exhibited a periodic switching strategy, allowing him to pay just enough attention to assist the automation when needed. Indeed, four of the five top performers were distracted more than one-third of the time. These findings suggest that distraction due to boring, low task load environments can be effectively managed through efficient attention switching. Future work is needed to determine optimal frequency and duration of attention state switches given various exogenous attributes, as well as individual variability. These findings have implications for the design of and personnel selection for supervisory control systems where operators monitor highly automated systems for long durations with only occasional or rare input.

Keywords: human supervisory control, decentralized systems, human-computer interface, smart grid, decision support, power plantsIn the push to develop smart energy systems, there is increasing focus on how to design systems that measure and predict user behavior in order to effect optimal energy consumption. While such focus is clearly an important component in the success of these future systems, substantially less attention is paid to the human on the other side of the energy system loop -the supervisors of power generation processes, the proverbial men (or women) behind the curtain. Out of sight and sadly in terms of technological advancements, out of mind, today these operators perform high risk jobs in often datarich, but information-impoverished settings. For these operators, pervasive computing of the future will likely add to an already complex array of data streams, and introduce a new layer of supervisory complexity in response to the goal of dynamically adapting energy management.The Three Mile Island nuclear power plant accident in 1979 was caused primarily by operator misunderstanding of sensor data from an overwhelmingly complex control panel [1]. More recently in 2003 in the Northeast, operators were not able to both see and understand critical system states for nearby power grids, ultimately leading to the largest blackout in North American history which contributed to at least 11 deaths and cost an estimated $6 billion [2]. In these high profile cases, and in countless other more minor electric and nuclear power plant incidents, a significant problem was and continues to be the lack of explicit design to support rapid data aggregation and information visualization to support supervisors' time-pressured decision making.The development of smart energy systems that leverage pervasive computing could further add to the workload of these supervisory control operators who will have to predict possible power plant load and production changes due to environmental and plant events, as well as dynamic system adaptation in response to customer behaviors. Contrary to many assumptions, the insertion of more automation, both in terms of distributed sensors and algorithms to post-process data for operators, will not necessary reduce workload, nor necessarily improve system performance. These concepts are explored in more detail in the following sections. Supervisory Control and Workload in Power GenerationCurrent power generation operations are highly automated. In normal, day-to-day operations, automation controls the adjustment of system parameters, while human operators generally take the role of system supervisors, monitoring system states and typically intervening in only non-monitoring operations, such as responding to an alarm, managing a plant start-up, or overseeing other off-nominal operations. However, in present-day power generation operations, while the system itself is highly automated, little automation is used to support and augment supervisor decision-making and performance, especially in time...

Of a thesis submitted in partial fulfillment of the requirements for the Doctor of Philosophy degree in Industrial Engineering in the Graduate College of

<p class="MsoNormal" style="text-align: left; margin: 0cm 0cm 0pt; layout-grid-mode: char;" align="left"><span class="text"><span style="font-family: ";Arial";,";sans-serif";; font-size: 9pt;">In the 2006 RoboCup Virtual Rescue Robots competition, teams from different research labs developed methods for controlling teams of mobile robots in a simulated urban search and rescue scenario. The scoring procedure used in this inaugural competition rewards participants for the number of victims found, the amount of area explored in the environment, the quality of the maps created by the robot teams and penalties participants for colliding with a victim or relying on human operators. The analysis of the strategies and scores suggests that the scoring procedure may lead teams to adopt strategies that are not consistent with the needs of a real search and rescue scenario. This paper introduces Robotic Exploration Utility as a measure of exploration quality and analyzes the results of the competition based on this measure. Individual robot contributions to the system were reviewed to account for the costs associated with adding a robot to the environment, indicating that value added per robot is an important measure that is overlooked. The analysis also revealed substantial performance variation, depending on the behavior that was being rewarded, which may indicate a lack of focus for evaluative performance measures of robotic urban search and rescue systems. The Robotic Exploration Utility metric enables the research community to focus on a performance measure which reflects the needs of the domain, while allowing task performance to be easily compared across systems.</span></span><span style="font-family: ";Arial";,";sans-serif";; font-size: 9pt;"></span></p>

In the 2006 RoboCup Virtual Rescue competition, teams from different research labs developed methods for controlling teams of mobile robots in a simulated urban search and rescue scenario. This paper reviews the strategies and scores from the top six competitors. The scoring procedure used in this inaugural competition rewards participants for the number of victims found, the amount of area explored in the environment, the quality of the maps created by the robot teams and penalties participants for colliding with a victim or relying on human operators. The analysis of the strategies and scores suggests that the scoring procedure may lead teams to adopt strategies that are not consistent with the needs of a real search and rescue scenario. Individual robot contributions to the system were reviewed to account for the costs associated with adding a robot to the environment, indicating that value added per robot is an important measure that is overlooked. The analysis of the impact of human operator penalties on scoring revealed an overemphasis on fully autonomous robotic systems. The analysis also revealed substantial performance variation, depending on the behavior that was being rewarded, which may indicate a lack of focus for evaluative performance measures of robotic urban search and rescue systems. The competition has the potential to provide influential research in this area if a proper scoring procedure that reflects actual research needs is implemented. In order to ensure that research gains made as a result of the competition process are useful to the application community, it is essential that the rules be tuned to the application needs. It is likely that, as competitions and games are becoming a growing part of the research community, this sensitivity is managed along with the other political, social and interactive demands involved in setting rules for research competitions.

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Objective Assess operator performance in a simulation of US Coast Guard small boat recovery to a larger vessel on a large scale, six degree-of-freedom, full motion simulator. Background Studies of human performance in small boat recovery task have never been conducted on a high amplitude, low frequency simulator. Empirical evidence of small boat recovery task performance in challenging motion conditions is needed to inform future maritime systems designs. Method Experienced active-duty boat crewmembers ( N = 13) conducted a small boat recovery task in three sea states on the Vertical Motion Simulator (VMS) at the NASA Ames Research Center. Task performance was assessed using a task equivalent for time to complete the task. Participant behaviors associated with increasing motion severity were observed. Results Task performance declined as motion conditions became more severe. Participants were more likely to use at least one hand to maintain balance during motion conditions, becoming more frequent with increasing motion severity. Many participants used one hand to complete the task despite contrary instructions and previous experience. Conclusion Two design recommendations were proposed to counter declining task performance in increasingly severe motion conditions. Handholds available to participants during the task, and task design supporting single handed completion were recommended for small boat recovery systems. Application This research is directly applicable to gross motor tasks requiring simultaneous maintenance of balance in a maritime environment, and may be extended to other environments where humans experience complex motions while completing tasks.

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