Decision Tool for Optimal Unmanned Vehicle Team Sizing
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Solution Overview
Problem
In Network Centric Operations, the increasing ratio of Unmanned Vehicles (UVs) to operators leads to information overload, causing loss of situation awareness due to inadequate system design, necessitating predictive models for human and system performance to determine optimal team size for mission scenarios.
Innovation Solution
A computer decision tool that includes a system performance module and an operator performance module, interacting to provide signals for an operator capacity decision module, which recommends an adequate team size by considering interface usability, automation level, algorithm efficiency, task management efficiency, and decision-making strategy variables.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the ratio of UVs to operators is increased to improve productivity, then more UVs can be controlled by a single operator, but information overload occurs causing loss of situation awareness
Solution Approach 1:
The patent introduces a computer decision tool as an intermediary between the operator and multiple UVs. This tool includes a system performance module that receives data from multiple UVs and an operator performance module that models operator capabilities, acting as a mediator that processes information before presenting it to the operator, thereby enabling control of more UVs without overwhelming the operator
Solution Approach 2:
The patent replaces the direct human cognitive processing of multiple UV data streams with an automated computer-based decision support system. The system performance module and operator performance module use computational models to assess system status and operator capacity, substituting mechanical/cognitive human processing with automated information processing capabilities
2Adaptability or versatility
If C2 technologies are developed to allow operators to control multiple UVs, then the ratio of UVs to operators can be increased, but systems may be used beyond their design capabilities causing operator overload
Solution Approach 1:
The patent implements dynamic adjustment of system capabilities based on real-time operator performance assessment. The operator performance module continuously evaluates operator capacity and adjusts the number of UVs the operator can effectively control, allowing the system to adapt to varying operator states and prevent overload while maintaining versatility
Solution Approach 2:
The patent incorporates feedback loops where the system performance module receives data from UVs and the operator performance module assesses operator status, which then feeds back to adjust the configuration of UV-operator teams. This feedback mechanism ensures the system operates within reliable boundaries while maximizing adaptability
3Quantity of substance
If the number of UVs is increased for a mission scenario, then mission coverage is improved, but operator workload increases leading to information overload
Solution Approach 1:
The patent segments the complex task of controlling multiple UVs into distinct functional modules: the system performance module that handles UV data collection and processing, and the operator performance module that manages operator capacity assessment. This segmentation allows the system to handle larger numbers of UVs by dividing the complex control function into manageable components
Data Source
AI summary
The present invention is a computer decision tool for use in a system for controlling a team of unmanned vehicles. The computer decision tool includes a system performance model for receiving interface usability, automation level and algorithm efficiency variables and an operator performance model. The operator performance model receives task management efficiency and decision making strategy or DM efficiency variables. The system performance model is responsive to the interface usability, automation level and algorithm efficiency variables for providing a system performance status signal. The operator performance model is responsive to task management efficiency and DM strategy variables for providing an operator performance status signal. An operator capacity decision model is responsive to the system performance and operator performance status signals and a workload variable for providing a decision signal representative of an adequate team size or an optimal recommendation, such as changing the team size.