Measuring situational awareness has been studied greatly in recent years, since situational awareness plays a critical role in decision-making processes, especially in the battlefield, where the commander's knowledge and understanding of the environment can be of vital importance to successfully accomplishing their missions. In the digital age, in which C4I Systems for improving situational awareness are developed, measuring this is even more necessary.
The Israel Defense Forces (IDF) Ground Forces Command Battle Laboratory (battle-lab) is a research oriented virtual environment, where active duty soldiers participate in a simulated combat on a large scale. This acts as an environment in which collecting data and control issues are easy to be dealt with. Over the last years, the battle-lab has developed a method for measuring situational awareness with a unique quantitative objective index.
Collecting the data was carried out on a digital map, in which during a warfare scenario participants marked situational factors while in action. The data addressed their perceived geo-location, friendly forces, and enemies. Every measurement was documented with exact time stamp and location, allowing it to be compared to what the “real situation” was in the simulation.
Analysis of the data was made by translating the differences between the participants' marks and the real situation to a quantitative value, by using deterministic algorithm and a machine learning algorithm based on expert assessments. This method brings a simple computer-based process to measure situational awareness and get it as an objective, quantitative rate.
This method of measuring and examining situational awareness will be presented in this paper, along with the results and the analysis of the process applied during an experiment conducted at the battle-lab in February of 2018.