## 2 Background
### Vehicle Systems: The Role of Road Friction  
As remarked by several authors, the knowledge of the road friction potential \(\mu_{\max}\) can contribute significantly to the enhancement of vehicle systems [14; 15; 23; 36; 37; 77; 78]. According to [23], the enhancement of vehicle systems can benefit largely the driver, and in an upper level, the society (e.g., improved traffic safety/accident prevention). The author provides a diagram where it is showed how the collection and distribution of road friction information can benefit several applications, Figure 8.  
In particular, [PERSON] [23] highlights that such applications can be summarised into _driver information systems, vehicle dynamic control systems, Advanced Driver Assistance Systems (ADAS)_, and _co-operative applications_. In this subsection, the focus lies on discussing how the road friction estimation can enhance the performance of vehicle systems, and in particular, Advanced Driver Assistance Systems (ADAS). For additional discussion on the rest of applications, [PERSON] [23] can be consulted. In Figure 9 the influence of the road friction potential information on different vehicle systems is provided. Well-known chassis systems such as Anti-lock Braking System (ABS), Traction Control System (TCS), and Electronic Stability Program (ESP) are situated at the lowest level. Such systems already compute an estimation of the road friction potential to adjust their thresholds during high dynamic excitation. An accurate _a priori_ knowledge of the road friction potential might enhance the performance of these systems during the beginning of the intervention (e.g., brake pressure modulation during the first cycles of the ABS), but apart from this, a significant improvement would not be seen [23]. On the other hand, current ADAS such as Autonomous Emergency Braking (AEB) [26] or Adaptive Cruise Control (ACC) [25] depend strongly on the road grip potential and therefore are situated in a higher level. These systems rely on an _a priori_ knowledge of the road friction potential to compute the minimum separation distance (i.e., safety distance) between the ego and a preceding vehicle. A wrong assumption of the true road grip potential can lead to a severe collision or to a false unwanted intervention [77]. Moreover, in this case, the road grip potential must be estimated during regular driving conditions in which the lateral or longitudinal excitation is reduced (e.g., free-rolling driving). This complicates significantly the applicability of traditional slip-based approaches on the previous ADAS. Figure 8: Benefit of the collection and distribution of the friction information on several applications. Diagram adapted by the authors from [PERSON] [23]. Finally, novel ADAS systems such as Autonomous Drift Control (ADC) [22; 27; 30], Figure 10, are situated at the highest level. This system has been proposed by the authors with the aim to maximise the vehicle cornering performance on loose surfaces of limited manoeuvrability (e.g., gravel, deep snow [29; 31]) and is inspired by previous research works on automated drift control [29; 79] and agile manoeuvring [80; 81]. In particular, the most recent ADC system developed by the authors [30] coordinates individual wheel torque inputs from in-wheel electric motors [82; 83; 84; 85; 86] and the steering wheel angle from an Active Front Steering (AFS) system to stabilise the vehicle around large body slip angles. The first results indicate that the correct estimation of the road-friction characteristics has a large impact on the drift  
Figure 10: A promising novel ADAS system for vehicle manoeuvrability enhancement on loose surfaces: Autonomous Drift Control (ADC) [22; 27; 30]. Figure 9: Impact of the road friction potential estimation \(\mu_{\max}\) on different generations of vehicle systems. Current vehicle systems (e.g., ABS) are less dependent on the _a priori_ road friction information than current (e.g., AEB) or expert ADAS (e.g., ADC). stabilisation.