## 4 Self-Organizing Maps Applied to Driving-Behavior Classification
### SOM-Based Drivers Grouping Regarding Fuel-Consumption
#### 4.3.1 SOM Classification Results
* Low fuel consumption (blue) corresponds to drivers who use the gas pedal gently and run the car at medium regimes (low PGP, low GP, and medium ERPM). * Medium-High fuel consumption (green) corresponds to drivers who use the gas pedal extensively and run the car at high engine regimes (high PGP, disperse GP, and high ERPM). Nevertheless, despite interesting DS-related fuel consumption profiles being extracted at a joint interpretation of the information that is depicted in Figure 9 and Table 4, driver classification cannot be \begin{table}
\begin{tabular}{l c c c} \hline \hline
**Cluster Label** & **Average Value** & **Variance** & **Maximum Value** \\ \hline Very low (red) & 2.76 & 1.02 & 6.66 \\ Low (blue) & 3.04 & 1.53 & 7.80 \\ Medium-High (green) & 5.15 & 3.34 & 12.6 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Fuel consumption (L/100 km) parameters of the three-cluster classification. Figure 9: Three-dimensional views of the three-cluster fuel consumption classification results. The clusters were labeled as Very low (red), Low (blue), and Medium-High (green). (**a**) Displays the cluster distribution considering PGP, ERPM and GP. (**b**) Considers PGP, ERPM and XACC var. (**c**) Displays clusters regarding PGP, GP and XACC var, and (**d**) considers ERPM, GP and XACC var. kept uniform along an entire trip, since it is far from being a binary task. For that reason, due to driving circumstances changing during a trip, evaluation by time windows provides a better assessment of the fuel consumption trend. In Table 3, the distribution of DS among clusters is displayed. As can be seen, each driver shows a unique cluster distribution for his/her trip. This distribution means that fuel-consumption-related DS is not a binary feature, but a composition of several cluster mixture ratios. Four drivers stand out among the remaining ones: D1, D6, D11, and D14, as remarked in bold in Table 3. Thus, D6 and D11 spend a longer time classified with Very low consumption DS, with 80.2% and the 78.6% of the total ride time, respectively, so they can be considered as eco-friendly drivers. On the other hand, D1 and D14 are the opposite case, with 75.3% and 66.3% of the total ride time being classified as Medium-High fuel consumption drivers, totally compromising eco-friendliness. According to the clusters identified in Figure 9, while the former drivers operate the throttle pedal uniformly and keep engine RPMs low, being an ideal operation decision, the latter ones swiftly operate the gas pedal and keep engine RPMs at the upper range for most of the trip. Finally, it is worth remarking that most drivers' behavior evolves between contiguous classes, except D10, which exhibits a particular behavior, leaping between extreme classes (from Very low to Medium-High, and vice versa). Table 5 compiles the actions drivers should perform to modify their DS with the aim of reducing their fuel consumption attending to their current classification. Different actions are needed, depending on the group, as can be seen in this table. Thus, for example, since Medium-High fuel consumers typically operate the gas pedal swiftly, keeping RPMs high due to that aggressiveness, they are required to lower RPMs while trying to operate the gas pedal smoothly and to a lesser extent. On the other hand, low consumption drivers are required to switch to a higher gear because, despite their softly operating the gas pedal, they keep RPMs high due to the use of low gears. Finally, very low fuel consumers are required to keep their DSs with no changes. The recommendations that are indicated in Table 5 could be unclear for some drivers, especially those being classified into the green cluster (Medium-High consumption). For that reason, with the aim of personalizing the driving recommendations, SOM clustering of the trained map was recomputed using a lower threshold value in its U-matrix, so that more precise partitions could be obtained.