Advancing Situation Awareness Systems:Evaluating Decision-Making Methods with UAV Applications

Situation awareness (SA) refers to the perception of environmental elements within a specific volume of time and space, understanding their meaning, and projecting their near future status. This model has three levels: perception of the current situation, comprehension of the current situation, and projection of future status. SA is a term used to describe an individual’s level of awareness and understanding of "what is happening". Therefore, SA serves as the first step in decision-making, providing an understanding of "what is happening" and "what is likely to happen". In practice, safe decision-making depends on the continuous extraction of technical and environmental information, integrating knowledge, and forming a coherent mental picture to guide perception and predict future events. The use of this concept is essential for several reasons. First, situation awareness systems improve the accuracy of decisions by providing up-to-date and comprehensive information about the environment. These systems, by delivering precise data and analyses, reduce human errors and ensure that decision-makers consider all relevant factors and data, leading to more accurate decisions. Moreover, situation awareness increases decision-making speed. These systems quickly identify environmental changes and process large volumes of data in a short time, providing decision-makers with relevant information rapidly, which leads to timely and swift decisions.In recent years, the application of SA has gained prominence in Unmanned Aerial Vehicles (UAVs), where continuous extraction of technical and environmental information is vital for safe and efficient operations. UAVs rely on real-time data integration to form coherent mental models that guide perception, enhance decision-making, and predict future events, thus improving operational safety and efficiency. The use of SA systems in UAVs is essential for several reasons. First, they enhance decision accuracy by providing comprehensive, up-to-date information about the environment, reducing human errors and ensuring that all relevant data are considered, and increases decision making speed. Hence, in this paper, we examine and evaluate various decision-making methods in situation awareness systems by focusing on UAV application. Situation awareness (SA) refers to the perception of environmental elements within a specific volume of time and space, understanding their meaning, and projecting their near future status. This model has three levels: perception of the current situation, comprehension of the current situation, and projection of future status. SA is a term used to describe an individual’s level of awareness and understanding of "what is happening". Therefore, SA serves as the first step in decision-making, providing an understanding of "what is happening" and "what is likely to happen". In practice, safe decision-making depends on the continuous extraction of technical and environmental information, integrating knowledge, and forming a coherent mental picture to guide perception and predict future events. The use of this concept is essential for several reasons. First, situation awareness systems improve the accuracy of decisions by providing up-to-date and comprehensive information about the environment. These systems, by delivering precise data and analyses, reduce human errors and ensure that decision-makers consider all relevant factors and data, leading to more accurate decisions. Moreover, situation awareness increases decision-making speed. These systems quickly identify environmental changes and process large volumes of data in a short time, providing decision-makers with relevant information rapidly, which leads to timely and swift decisions. In recent years, the application of SA has gained prominence in Unmanned Aerial Vehicles (UAVs), where continuous extraction of technical and environmental information is vital for safe and efficient operations. UAVs rely on real-time data integration to form coherent mental models that guide perception, enhance decision-making, and predict future events, thus improving operational safety and efficiency. The use of SA systems in UAVs is essential for several reasons. First, they enhance decision accuracy by providing comprehensive, up-to-date information about the environment, reducing human errors and ensuring that all relevant data are considered, and increases decision making speed. Hence, in this paper, we examine and evaluate various decision-making methods in situation awareness systems by focusing on UAV application.

کلیدواژه ها:

Situation Awareness ، Decision-making ، Unmanned Aerial Vehicles (UAVs) ، Heuristic based methods ، Model based methods ، Data driven methods