http://hdl.handle.net/1721.1/46717 2013-05-24T11:14:32Z http://hdl.handle.net/1721.1/46752 Integrating Multiple Alarms & Driver Situation Awareness Cummings, M. L.; Wang, Enlie; Ho, Angela W. L. This study addresses this gap in CAS and intelligent alarm research by examining whether or not a single master alarm warning versus multiple warnings for the different collision warning systems conveys adequate information to the drivers. Intelligent driver warning systems signaling impending frontal and rear collisions, as well as unintentional lane departures were used in this experiment, and all the warnings were presented to drivers through the auditory channel only. We investigated two critical research questions in this study: 1. Do multiple intelligent alarms as opposed to a single master alarm affect drivers’ recognition, performance, and action when they experience a likely imminent collision and unintentional lane departure? 2. Is driver performance and overall situation awareness under the two different alarm alerting schemes affected by reliabilities of the warning systems? 2006-01-01T00:00:00Z http://hdl.handle.net/1721.1/46751 Mitigation of Human Supervisory Control Wait Times through Automation Strategies Mitchell, P. J.; Cummings, M. L.; Sheridan, T. B. The application of network centric operations principles to human supervisory control (HSC) domains means that humans are increasingly being asked to manage multiple simultaneous HSC processes. However, increases in the number of available information sources, volume of information and operational tempo, all which place higher cognitive demands on operators, could become constraints limiting the success of network centric processes. In time-pressured scenarios typical of networked command and control scenarios, efficiently allocating attention between a set of dynamic tasks is crucial for mission success. Inefficient attention allocation leads to system wait times, which could eventually lead to critical events such as missed times on targets and degraded overall mission success. One potential solution to mitigating wait times is the introduction of automated decision support in order to relieve operator workload. However, it is not obvious what automated decision support is appropriate, as higher levels of automation may result in a situation awareness decrement and other problems typically associated with excessive automation such as automation bias. To assess the impact of increasing levels of automation on human and system performance in a time-critical HSC multiple task management context, an experiment was run in which an operator simultaneously managed four highly autonomous unmanned aerial vehicles (UAVs) executing an air tasking order, with the overall goal of destroying a pre-determined set of targets within a limited time period. Four increasing levels automated decision support were investigated as well as high and low operational replanning tempos. The highest level of automation, management-byexception, had the best performance across several metrics but had a greater number of catastrophic events during which a UAV erroneously destroyed a friendly target. Contrary to expectations, the collaborative level of decision support, which provided predictions for possible periods of task overload as well as possible courses of action to relieve the high workload, produced the worst performance. This is attributable to an unintended consequence of the automation where the graphical visualization of the computer’s predictions caused users to try to globally optimize the schedules for all UAVs instead of locally optimizing schedules in the immediate future, resulting in them being overwhelmed. Total system wait time across both experimental factors was dominated by wait time caused by lack of situation awareness, which is difficult to eliminate, implying that there will be a clear upper limit on the number of vehicles that any one person can supervise because of the need to stay cognitively aware of unfolding events. 2005-01-01T00:00:00Z http://hdl.handle.net/1721.1/46750 Conceptual Human-System Interface Design for a Lunar Access Vehicle Smith, Cristin; Essama, Stephane; Duppen, Mark; Marquez, Jessica; Cummings, Mary; Wang, Enlie In support of the vision for humans to establish a large scale, economically viable, permanent human settlement on the Moon within the next 25 years (Space Frontier Foundation, 2005), the next generation lunar landing vehicle must be capable of achieving pinpoint, anytime, anywhere safe landing on the lunar surface with high precision (10- 100m). In addition, this vehicle should support both autonomous and manned lunar missions (NASA ASO-1160). Because of advances in technology over the past thirty-five years since the Apollo landings, the role of the human and automated systems in a new lunar lander system must be reevaluated and redesigned. This report details the design approach and resultant preliminary, conceptual design concepts for a Human-System Interface (H-SI) for a Lunar Access Vehicle (LAV). 2005-01-01T00:00:00Z http://hdl.handle.net/1721.1/46749 Decision Support Design for Workload Mitigation in Human Supervisory Control of Multiple Unmanned Aerial Vehicles Brzezinski, A. S.; Cummings, M. L. As UAVs become increasingly autonomous, the multiple personnel currently required to operate a single UAV may eventually be superseded by a single operator concurrently managing multiple UAVs. Instead of lower-level tasks performed by today’s UAV teams, the sole operator would focus on high-level supervisory control tasks such as monitoring mission timelines and reacting to emergent mission events. A key challenge in the design of such single-operator systems will be the need to minimize periods of excessive workload that could arise when critical tasks for several UAVs occur simultaneously. To a certain degree, it is possible to predict and mitigate such periods in advance. However, actions that mitigate a particular period of high workload in the short term may create long term episodes of high workload that were previously non-existent. Thus some kind of decision support is needed that facilitates an operator’s ability to evaluate different options for managing a mission schedule in real-time. This paper describes two decision support visualizations designed for supervisory control of four UAVs performing a time-critical targeting mission. A configural display common to both visualizations, named the StarVis, was designed to highlight potential periods of high workload corresponding to the current mission timeline, as well as “what if” projections of possible high workload periods based upon different operator options. The first visualization design allows an operator to compare different high workload mitigation options for individual UAVs. This is termed the local visualization. The second visualization is indicates the combined effects of multiple high workload mitigation decisions on the timeline. This is termed the global visualization. The main advantage of the local visualization is that options can be compared directly; however, the possible effects of these options on the mission timeline are only indicated for the individual UAV primarily affected by the decision. For the global visualization, different decisions can be combined to show possible effects on the system propagated across all UAVs, but the different alternatives of a single decision option alternative cannot be directly compared. An experiment was conducted testing these visualizations against a control with no visualization. Results showed that subject using the local visualization had better performance, higher situational awareness, and no significant increase in workload over the other two experimental conditions. This occurred despite the fact that the local and global StarVis displays were very similar. Not only did the Global StarVis produce degraded results as compared to the local StarVis, but those participants with no visualization performed as well as those with the global StarVis. This disparity in performance despite strong visual similarities in the StarVis designs is attributed to operators’ inability to process all the information presented in the global StarVis as well as the fact that participants with the local StarVis were able to rapidly develop effective cognitive problem strategies. This research effort highlights a very important design consideration, in that a single decision support design can produce very different performance results when applied at different levels of abstraction. 2006-01-01T00:00:00Z