## 4 Discussion  
Research on the trade-off between humans and automation has been conducted in [48], in which the authors claimed that only with a proper design of the cooperative human-machine systems will technological advances make our lives easier, safer, and more enjoyable rather than harder and more uncomfortable. In fact, combining the individual strength of the different partners can create a fruitful symbiosis between humans and technology, where the automated system can play an important role, but still has to serve the human. In [49], [PERSON] et al. selected haptic shared control to achieve a smooth collaboration between humans and automated systems in a lane-keeping maneuver, because this channel can facilitate mutual communication [50; 51]. Keeping that in mind, we have been inspired by the work of [PERSON] and colleagues [9], since their research also faced the challenge of determining a combination that preserves the best performance features of human and automatic control in a cooperative manner. In this work, the authors used a driving simulator to investigate the ability of human-automation teams to cover for human and automation faults (the goal was to avoid obstacles), developing an MPC and considering two baseline conditions. In our work, we extended the automation support, considering distracted drivers and also investigating the cooperation of human and automation (that is, of the team) when one of the members has limited resources (e.g., the human driver is inattentive). We have adopted an NMPC approach, considering experiments at a driving simulator with real users. Additionally, the NMPC-based shared controller proposed in this work offers a novel design in terms of stability criteria under different levels of authority (which is no longer dimensionless, but with torque units, which allows a more intuitive selection of its value). Furthermore, we have considered an appropriate methodology for sharing a given task, which is important to achieve effective vehicle control, presenting two design considerations in the arbitration module (i.e., minimal intervention and safety-over-comfort). Moreover, in comparison with a similar work that also studied shared control for the scenario of a distracted driver [22], the quantitative results show consistency overall. In terms of controller performance without driver intervention, both lateral error RMSs are under 10 cm. In the tests with real drivers, both works show an improvement on lateral error RMS during the distraction event when using SC (adaptive authority). However, our work showed improved performance during normal driving in comparison with MANUAL, while the cited work showed similar performance, which is expected to be caused by a difference in how SC behaves when the driver is concentrating (their work recreates manual driving, while ours gives a low assistance torque up to 1 Nm (see Figure 8e). In terms of driver efforts, the cited work shows the highest effort in SC while performing the secondary task, while our findings indicate lower efforts using SC compared with LC and MANUAL. In addition, we have also drafted a qualitative analysis regarding how drivers perceive this cooperative system, and SC had the higher scores in terms of safety and comfort, which is similar to the subjective results obtained in the aforementioned work. As an additional point in this discussion, it is important to underline here that--as stated in [52]-- humans are constantly assessing trustworthiness, and therefore an effective human-machine system must be trustworthy, because \"no trust, no use\" [53]. In this paper, trustworthiness is defined as a dispositional and relational property of agents relative to other agents within spatiotemporal bounds. In other words, humans tend to trust (artificial) agents that operate within the bounds of human cognition and are less trusting of systems that operate at superhuman levels.