## 3 Slip-Based Road Friction Monitoring  
The estimation of the road friction potential from signals that are already available on the CAN bus of modern vehicles has been extensively investigated in the literature. The major common point of these strategies is that the friction potential is extracted from a rubber-road friction model such as described in Section 2.2.3. In brief, the tyre forces and the tyre slips are observed from the vehicle dynamics (e.g., using a state estimator) and employed in a friction model. The maximum friction potential \(\mu_{\max}\) is then inferred from the difference between the reconstructed forces and the forces provided by the model for the current tyre slip values. Depending on the approach considered, the friction model can take the form of an analytical expression (e.g., _Brush_ model [87; 88]) or a Neural Networks structure [3; 10; 68]. The main drawback derived from this methodology is that a certain longitudinal or lateral slip is necessary in order to accomplish such estimation. In Figure 11a the tyre longitudinal forces obtained from a parameterised _Magic Formula_ 6.1 tyre model [3] are depicted. As can be noticed, the slope of these forces does not change significantly between high and low adherence rigid road surfaces (e.g., dry asphalt, wet asphalt) when the longitudinal excitation is kept low (i.e., negligible \(C_{\lambda}\) difference is observed between \(\mu_{\max}=1\) and \(\mu_{\max}=0.6\) for \(\lambda<2\%\)). This behaviour is derived from the infinitely rigid road assumption employed to formulate the _Brush_ and _Magic Formula_ tyre models [67]. As a consequence, the slope of the tyre forces is considered only a function of the tyre tread stiffness in these models, and is not affected by the \(\mu_{\max}\) coefficient. This has been evidenced experimentally under well-controlled braking tests performed in a wide range of rigid surfaces by [PERSON] et al. [45]. Nevertheless, in a large number of works the previous statement is refuted and the so-called \"slip slope\" concept is presented. In particular, the slip slope idea states that the tyre longitudinal stiffness (slope on Figure 11a) presents significant variations between high and low adherence surfaces. In these works it is claimed that the slip slope tyre phenomena facilitate the estimation of the friction potential under minimum excitation levels using traditional slip-based approaches. As this approach is often tested on rigid as well as loose surfaces (e.g., snow, dry asphalt, ice, and gravel) the change in the slip slope might be induced by the soft material (e.g., sand) deposited between the tyre and the rigid road [17]. Moreover, the slip slope presents significant variations depending on external tyre parameters, such as the tyre pressure or the tyre wear [6; 7]. As a certain degree of controversy exists around the slip slope idea, these results are considered in more detail in the following sections. Leaving aside the slip slope discussion, this survey evidences that a non-negligible grip consumption level is always required to estimate the road friction potential. This limits the performance of slip-based strategies during free-rolling driving conditions. Some studies presented in this survey indicate grip consumption levels that range from 30% to 80 %. Lowest values are observed when tyre SAT-based approaches are employed due to the higher sensitivity of the former signal to variations in the lateral slip (i.e., earlier tyre SAT saturation, Figure 11b) [9,38] (See Section 3.3). In spite of these drawbacks, slip-based road friction monitoring is cost-effective and generally computationally inexpensive. Moreover, it can provide an accurate online estimation when enough excitation is present (e.g., during ABS or ESP intervention). The main aim of this discussion is to provide some clarity regarding the minimum grip consumption thresholds required by the most relevant slip-based approaches existing in the literature.