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Command, Control and Communication Techniques for Reliable Assessment of Concept Execution



The U.S. Army is in the midst of a revolutionary transformation, and the Future Combat System (FCS) initiative is at the center. Information access and distribution will be critical to mission success. At the same time, this information-rich environment is certain to provide many challenges for the Command, Control, and Communication (C3) environment. In order to improve a warfighter's ability to filter and select important information, an improved understanding of information systems and their interaction with organizational structures must be developed. Concepts for the organizational, personnel, and technology needs within the FCS-equipped organization cannot all be examined in live simulations and exercises. Constructive simulations and Human Performance Models (HPMs) are necessary to analyze which organizational, personnel, and system architectures produce the greatest efficiency and effectiveness for decisive victory. Of vital interest, particularly in the analysis of FCS C3 organizations, is the capability to assess the quality of decisions made by the personnel.



The military command and control process is certain to change given the introduction of new information technology and new organizational structures. To predict how these changes will impact system performance, ARL-HRED sponsored the MA&D Operation to develop a modeling environment in which one can develop multiple concept models for any sized organization, staffed by any number of people, performing any number of functions and tasks, and under various communication and information loads. This environment is called Command, Control, and Communication: Techniques for Reliable Assessment of Concept Execution (C3TRACE). Among the performance measures tracked are operator utilization, the number of tasks performed, and the quality of decisions made by the operators.



C3TRACE can be used to estimate the impact of "digitizing" the battlefield on decision making. In order to establish an accurate assessment of what decisions are being made, an 'Information Driven Decision Making' architecture provided by ARL-HRED was embedded into C3TRACE. There are 24 possible information elements, taken from the U.S. Army's accelerated decision-making process documentation. The information elements are grouped into six categories: (1) information about enemy force and actions, (2) information about friendly force and actions, (3) feasibility of the plan, (4) suitability of the plan, (5) information to judge acceptable risk, and (6) information on the enemy course of action and potential courses of action. These elements are attached to the communication events that trigger human tasks. The information accuracy level drives the operator's decision quality and is used to account for which operator knew what elements of information and how recent that information may be to the operator.


The information used to make a decision is further adjusted according to two factors: the accumulated "information decay" and the match between available information and the information required to make a decision. The match between available information and the information required to make a decision occurs whenever a decision task is executed. Does the decision-maker have the right information, either processed directly from a message or received from a collaborator, to make a decision when the time comes? In the end, the "quality" of a decision, that is, the probability of making a good decision, is based on the match between the information received by the decision maker and the information required to make a decision and also by how much the "value" of the information has decayed over time. This technique can help to identify system and organizational inefficiencies, bottlenecks, or obstacles relevant to the high quality and recent information required for effective decision making.



In support of FCS, C3TRACE is being used to represent and evaluate differences between FCS concepts in baseline and alternate configurations of the Unit of Action (UA) Mounted Combat System Company Headquarters. The two configurations were conceptualized to use the same information technology, but differed as to the personnel configuration and vehicle. The focus of the model was on information flow and communication, particularly when the information flow leads to a decision. The communication events were the same for both configurations of the UA models and contained over 8,900 messages that represented a 96 hour scenario. Preliminary data collected from the two configurations included operator utilization and performance, completed vs. dropped messages, mental workload to include visual, auditory, cognitive, and psychomotor levels, and decision quality as a result of the probability of making a good decision based on the information flow and information quality.


Decision quality scores for both the baseline and alternate configurations resulted in four bad decisions. These decisions were made by the Commanding Officer (CO) in the baseline and by the Executive Officer (XO) in the alternate. The COís utilization decreased from the baseline to the alternate configuration due to a redistribution of responsibilities. In the alternate, the CO handled messages that concerned fighting the battle rather than directing it. The XO assumed some of the CO responsibilities in spending time with messages directing the battle. The XO also handled the messages from the platoons that concerned status, situation reports, and readiness condition.

This resulted in an elevated utilization rate for the XO.



Work is in progress to develop an algorithm for self-efficacy, training level, and uncertainty as it affects an operatorís decision-making ability. Additional factors that can affect information quality and cause uncertainty in decision making include unreliable/incomplete sensor data, communications and network status, display design quality, and mis-match of multiple sources of information. Future plans also include possible linkage to other modeling and simulation tools such as One Semi-Automated Forces (SAF) Testbed, Modeling Architecture for Technology, Research, and Experimentation (MATREX), or Atomic Components of Thought-Rational (ACT-R).

For more information on C3TRACE, please contact us at

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