# Evolving the Controller of Automated Steering of a Car in Slippery Road Conditions
## 4 Discussion  
Some of the best SAFs evolved on icy and snowy roads featured slight steering oscillations with frequencies of about 1-5 Hz. We cannot conclude whether these oscillations have a beneficial effect on  
Figure 10: The dynamics of the deviation from the center of the lane of the car steered by the sample best-evolved SAF shown in Equation (8) in snowy (\(\mu\) = 0.5) road conditions.  
Figure 9: The dynamics of the steering angle of the car steered by the sample best-evolved SAF shown in Equation (8) in snowy (\(\mu\) = 0.5) road conditions.  
the controllability of the car. Most likely, they appear as a result of a neutral genetic code in the evolved SAF: a code that has no (neither a beneficial nor a detrimental) effect on the behavior of the car. Indeed, these steering oscillations do not manifest themselves in an oscillating trajectory of the car, because, due to the slippery conditions, the front tires slip excessively and could not provide sharp directional control of the car. Consequently, the oscillations do not result in any measurable oscillations of the lateral acceleration of the car, which was a metric that we used in the calculation of the fitness of the evolved SAF. Therefore, the GP could not impose any selection pressure against the evolved SAF that results in these oscillations. Despite that, the oscillations apparently do not affect detrimentally the steering of the car. From the standpoint of the feasibility of the practical implementation of the evolved SAF on real cars, such oscillations might be highly undesirable due to the uncomfortable vibrations and accelerated wear of the tires and the components of the steering system of the car. We speculate that by modifying the fitness function--e.g., by introducing a third additive component (in addition to the area under the trajectory of the car around the center of the lane and the average of its lateral velocity) that explicitly reflects the severity of steering oscillations--we could discourage the GP from evolving oscillating steering functions.  
The realization of steering controllers in the real world could be done in two steps in accordance with the concept of evolutionary robotics [33]. The first step, as discussed in our work, involves the evolution of a generic steering solution on the software model of the car in TORCS. The second stage, intended to bridge the inevitable reality gap, could be implemented as an evolutionary adaptation of the evolved generic solutions to real cars in real-world environments.  
Also, in our discussion about the generality of the evolved SAF, we assumed the possibility to deploy a single, general SAF that could be good enough in any (slippery) road condition. The disadvantage of such an approach would be that such a general SAF might be somehow inferior to a dedicated SAF evolved for a particular road condition (as illustrated in Figure 8). On the other hand, the advantage is that the system is not required to determine (in a real time) the current (instant) road conditions, i.e., the current (instant) coefficient of friction between the tires and the road. Our assumption--supported by the fact that most of the existing driving aids activated in slippery road conditions, such as anti-locking brake systems, traction control, and electronic stability programs, rely on the detection of the slippage of the tires rather than on the actual coefficient of friction (one of the underlying reasons for such a slippage)--was that such a determination is rather challenging: it requires a significant computational (signal-processing) power; the obtained result is approximate, and it might be obtained in a limited number of driving situations. However, the recent advances in automotive control suggest that in the near future these challenges might be successfully addressed [34].