## 5 Conclusions  
This paper deals with the human-computer interaction topic, applied to the ADS in its interaction with a human driver. It is commonly accepted that ADS can bring benefits, mainly in terms of improved safety and enhanced mobility (i.e., for elderly people and persons with impairment). When the ADS approaches the limits of its own ODD, the system issues a TOR, and then the driver is asked to get back into the control loop in the \"appropriated\" time. This paradigm is unrealistic and difficult to understand because it implicitly depicts the human-vehicle system as a kind of \"finite state machine\", but there are some driving situations in which the optimal interaction strategy lies in sharing, at a certain level, the dynamic driving task. Therefore, we claim that a new approach is possible, where human and artificial system together form a team, with the goal to reach the destination in a safe way. In order to achieve that, we designed and implemented an intelligent and adaptive co-pilot, here represented by the arbitration and shared control algorithms, which is the enabler of the cooperation between human-agent and machine-agent: at each time step, it is able to decide the level of authority and thus how the driving task can be shared, depending on the external conditions, the available resources of the system, and the cognitive status of the driver. Considering the selected KPIs, the results show better performance of the combined team (human-automation), with respect to the baselines we considered (\"normal\" driving with ADAS and automated system as it is currently): the critical situations are reduced (\"critical\" means that an accident or near-accident event occurred) and there is also an improvement in the tracking performance and in the driving efforts. The benefits shown in the quantitative analysis have then been reflected in the qualitative analysis, as drivers evaluated the SC modality as the best from the four tested, given statements that categorize the system as safe, harmonious, less intrusive, and also with the sense that the driver had to participate in the driving task to a greater extent than with the LC mode (even with the support given by the SC mode). The last is relevant because one of the major drawbacks of SAE-L2 and SAE-L3 is over-trust in automation and poor take-over performance, respectively. In this sense, SC would improve the interaction by keeping the driver in the control loop, making clear the need for his/her participation in the vehicle control task, while benefiting from improved safety, performance, and comfort. To sum up, we propose a paradigm shift: from the \"boss\" (that commands) to the \"team\" (that cooperates and mutually helps). The first implies a rigid hierarchical structure (i.e., automation is supervised by the human), with separated responsibilities (either the system is in charge, or the human driver) and fixed, precise roles; the second approach instead implies the freedom to cooperate, with accountability towards other members (e.g., two-way communication) and the possibility to share extensive information, authority, and control, so that the decisions are moved to the maximum level of awareness and resource availability. Recalling the title of the paper, we can claim at the end that being a \"valuable member of the team\" is better than being \"the unique boss\": the adaptive co-pilot is the technological enabler of it, providing more accurate results in terms of performance, safety, trustworthiness, and comfort. Conceptualization, M.M., F.T., S.D., A.C., J.S., J.P.; methodology, M.M., F.T., S.D., J.S., J.P.; software, M.M., J.S., A.C.; validation, J.S., M.M., S.D. ; formal analysis, S.D., M.M., J.S., F.T. ; resources, J.P., S.D. ; data curation, M.M., J.S., S.D. ; writing--original draft preparation, M.M., F.T., S.D., J.S., J.P., E.I., A.C.; writing--review and editing, F.T., J.P., E.I., S.D., J.S. ; supervision, S.D., F.T., J.P., E.I.