Assessing Operator Strategies for Real-time Replanning of Multiple Unmanned Vehicles

Future unmanned vehicles systems will invert the operator-to-vehicle ratio so that one operator controls a decentralized network of heterogeneous unmanned vehicles. This study examines the impact of allowing an operator to adjust the rate of prompts to view automation-generated plans on system performance and operator workload. Results showed that the majority of operators chose to adjust the replan prompting rate. The initial replan prompting rate had a significant framing effect on the replan prompting rates chosen throughout a scenario. Higher initial replan prompting rates led to significantly lower system performance. Operators successfully self-regulated their task-switching behavior to moderate their workload.This research is funded by the Office of Naval Research (ONR) and Aurora Flight Sciences

Dynamic human-computer collaboration in real-time unmanned vehicle scheduling

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2010.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student submitted PDF version of thesis.Includes bibliographical references (p. 123-127).Advances in autonomy have made it possible to invert the operator-to-vehicle ratio so that a single operator can control multiple heterogeneous Unmanned Vehicles (UVs). This autonomy will reduce the need for the operator to manually control each vehicle, enabling the operator to focus on higher-level goal setting and decision-making. Computer optimization algorithms that can be used in UV path-planning and task allocation usually have an a priori coded objective function that only takes into account pre-determined variables with set weightings. Due to the complex, time-critical, and dynamic nature of command and control missions, brittleness due to a static objective function could cause higher workload as the operator manages the automation. Increased workload during critical decision-making could lead to lower system performance which, in turn, could result in a mission or life-critical failure. This research proposes a method of collaborative multiple UV control that enables operators to dynamically modify the weightings within the objective function of an automated planner during a mission. After a review of function allocation literature, an appropriate taxonomy was used to evaluate the likely impact of human interaction with a dynamic objective function. This analysis revealed a potential reduction in the number of cognitive steps required to evaluate and select a plan, by aligning the objectives of the operator with the automated planner. A multiple UV simulation testbed was modified to provide two types of dynamic objective functions. The operator could either choose one quantity or choose any combination of equally weighted quantities for the automated planner to use in evaluating mission plans. To compare the performance and workload of operators using these dynamic objective functions against operators using a static objective function, an experiment was conducted where 30 participants performed UV missions in a synthetic environment. Two scenarios were designed, one in which the Rules of Engagement (ROEs) remained the same throughout the scenario and one in which the ROEs changed. The experimental results showed that operators rated their performance and confidence highest when using the dynamic objective function with multiple objectives. Allowing the operator to choose multiple objectives resulted in fewer modifications to the objective function, enhanced situational awareness (SA), and increased spare mental capacity. Limiting the operator to choosing a single objective for the automated planner led to superior performance for individual mission goals such as finding new targets, while also causing some violations of ROEs, such as destroying a target without permission. Although there were no significant differences in system performance or workload between the dynamic and static objective 4 functions, operators had superior performance and higher SA during the mission with changing ROEs. While these results suggest that a dynamic objective function could be beneficial, further research is required to explore the impact of dynamic objective functions and changing mission goals on human performance and workload in multiple UV control.by Andrew S. Clare.S.M

Persistence Through Collaboration at Sea for Off-Shore and Coastal Operations

Collaboration (Bruzzone et al. 2013a, b, c, d, e, f) is often mentioned as an opportunity to develop new capabilities for autonomous systems; indeed this paper proposes a practical application where use this approach to enhance the autonomy of the systems during operations in coastal areas or around offshore platforms. The proposed case deals with developing a collaborative approach (Bruzzone et al. 2013a, b, c, d, e, f) among an USV (Unmanned Surface Vehicle) with several AUV (Autonomous Underwater Vehicles) to guarantee persistent surveillance over a marine area (Shkurti et al. 2012). Obviously, the proposed solution could be adopted also for defense and homeland security (Bruzzone et al. 2011a, b, 2010) as well as for archeological site protection in consistence with related cost analysis. The authors propose a technological solution as well as a simulation framework to validate and demonstrate the capabilities of this new approach as well as to quantify expected improvements