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Autonomy of unmanned systems refers to their ability to self-manage, make decisions, and complete tasks with minimal or no human intervention. The scope of autonomy ranges from zero to full capability, often defined through models, and encompasses four fundamental functions: perception, orientation, problem-solving (planning), and action. Advances in autonomy enable unmanned systems to learn, adapt to changing environmental conditions, and perform complex tasks, driving innovation in various fields.
There are several ways to classify autonomy levels based on various criteria. In 2014, the American organization Society of Automotive Engineers (SAE) International adopted a classification of six levels of autonomous driving, which was subsequently modified in 2016. Based on a decision by the National Highway Traffic Safety Administration (NHTSA), this is the officially applicable standardization in the United States, which is also the most popular in studies on autonomous driving technologies in Europe.
To clarify the situation, SAE International has defined 5 levels of automation for autonomous vehicles, which have been adopted as an industry standard (see Figure 1).
In general, autonomy or autonomous capability is defined in the context of decision-making or self-governance within a system. According to the Aerospace Technology Institute (ATI), autonomous systems can essentially decide independently how to achieve mission objectives, without human intervention [2]. These systems are also capable of learning and adapting to changing operating environment conditions. However, autonomy may depend on the design, functions, and specifics of the mission or system [3]. Autonomy can be broadly viewed as a spectrum of capabilities, from zero autonomy to full autonomy. The Pilot Authorization and Task Control (PACT) model assigns authorization levels, from level 0 (full pilot authority) to level 5 (full system autonomy), also used in the automotive industry for autonomous vehicles (see Figure ) [2].