### Our Answer: The Concept of the Adaptive Co-Pilot  
Given this picture, together with the fact that people like driving, humans will remain part of the system for a long time, with capabilities for driving a vehicle that are in large part complementary to the capabilities of automation systems. The human driver offers superior perception and judgment, is capable of making high-level decisions, and brings rich prior experience and the ability to generalize from one type of experience to another [9]. Thus, humans still need to recognize performance shortcomings in automated systems, decide whether to adopt or reject decisions recommended by automation, and react to cases not included in the ODD of the automated functions [15]. In this perspective, how to combine the capabilities of human and automatic drivers should be investigated carefully, as the transfer of control from the human driver to the automated driving system and vice versa needs to follow a safe and meaningful process that circumvents or even solves this difficulty. Since a clear division of transitioning control authority is difficult to find, a \"simple\" trading scheme where the control authority is given to whichever agent outperforms the other (in specific traffic situations or time intervals) cannot be enough. [PERSON] and [PERSON] [16] state that in the aforementioned situations, when the operational limits are reached, the driver must receive support and guidance, necessary to reenter the control loop [17]. However, smooth transfer of control authority between an automation system and a human is notoriously difficult (from the aviation domain, in human-automation teams, there can be errors during transfers of control authority, misinterpretation or misappropriation of responsibility, and loss of situational awareness [9; 18; 19]). Therefore, various schemes where vehicle control is shared (instead of traded) between the human and the automated system have been proposed [8; 20], but it is fundamental to understand how the automated system and the human driver can interact with each other, simply and naturally, requiring that agents can learn when to support and how to mediate joint actions in collaboration, with the long-term vision that automated cooperation among traffic participants can improve traffic efficiency and safety beyond the level attainable by only human drivers or only machine-agents [21]. Rather than complete transfers of control authority at discrete instants of time, the idea of the adaptive co-pilot attempts to form a cooperative \"team\" that involves the human and automation system working together simultaneously in the same task (known as the shared control scheme [8; 22]) with a variable intensity of intervention (i.e., authority) that depends on the driving context (e.g., in a low-complexity maneuver with a driver in proper conditions, the intervention of automation is low in torque amplitude, while in a scenario with a high risk of accident with a distracted driver, the automation intervention is higher). The expectation is that team performance would exceed the performance of either agent acting alone and cognitive workload would be reduced for the human [23]. In other words, the idea hereby developed is that driver and automation are regarded as members of a unique \"team\" that understand and support each other in cooperatively pursuing the goal of driving safely, efficiently, and comfortably. In this sense, to counteract the drawbacks present in vehicles SAE-L2 (over-trust, misuse of the system, and expecting something for which the system is not designed) and SAE-L3 (with the out-of-the-loop problems that produce poor drivers' take-over performance), this paper proposes the intelligent adaptive co-pilot as the enabler for a new cooperative framework between the machine-agent (automation) and the human-agent (driver).