The Impact of Message Quality on Entity Location and Identification Performance in Distributed Situational Awareness

Abstract

There are many organizations where location and time are critical to the success of their mission. These organizations desire to improve the performance of their teams with the technology they are using to locate an entity in the minimal amount of time as necessary. The study of this optimization is titled visual analytics, which studies the performance of humans and machines on a specific task. For this work, the task is detecting and identifying a specific entity, a team task consisting of two analysts, verbally communicating together in order to collaborate on completing their task. With the message quality of this communications impacting the outcome of their performance due to its effect on their situational awareness of the situation. To address this question, a simulated environment was created using the program FOCUS. This simulation replicated two unmanned aerial systems – operated by two human analysts (simulated), each carrying a different electro-optical sensor, over a complex, urban environment. A yellow taxicab acted as the specific entity the two analysts tried to detect and identify by utilizing targeting performance measures. This function was evaluated within the simulation against different levels of message qualities (low, medium, and high quality) that was incorporated into the same level of situational awareness and based on the training level of the team. These levels were measured 500 times for each level to determine the impact on the performance of the tasks. This was accomplished through the utilization of the distributed situational awareness theory. The results showed a significant difference between each level of situational awareness, impacted by message quality. It also supported that each level was significantly better than the result of the lower level. This provides additional evidence that training on communications improves the performance of the team and creates a baseline of performance based on situational awareness. When aided target recognition technology was incorporated into the experiments, however, the added technology did not produce significantly different performance results compared to the high level of situational awareness and training. For those organizations that location and time are important to mission accomplishment, these results provide an additional resource on the how technology and training might be utilized to find the best performance given certain situations. A highly trained team might improve their performance with this technology, or a team with low training could perform at a high level given the appropriate technology in limited time scenarios. More importantly, this provides an evaluation tool to compare new technologies and their impact on teams. Is an investment in new technology appropriate if investing in additional training produces the same performance results? Future performance can also be evaluated based on the team’s level of training and use of technology for these specific tasks.