# Improving Machine Learning Identification of Unsafe Driver Behavior by Means of Sensor Fusion
## 4 Experimental Results
### Analysis of the Proposed Features  
In order to qualitatively evaluate the adequacy of the features in describing different driving behaviors, the scatter plots of some of these have been reported. Notice that when the record is labeled as unsafe, the value of the point identified by the corresponding couple of features is represented by a red triangle and by a blue circle when it is labeled as safe.  
**In-vehicle sensors' features:** Figure 3 reports the plot of the maximum value of the engine rotation speed versus the maximum value of the vehicle speed. It is clearly visible that high engine speeds are more frequently associated with unsafe behaviors when the vehicle speed is high rather than when it is low. This is essentially due to the fact that a common behavior is driving at relatively high engine speeds when a low gear is engaged (for example, during departures or whenever the vehicle needs to increase speed), so that it is not a symptom of aggressive driving. On the other hand, high engine speed, when a high gear is engaged, can be frequently associated with unsafe behaviors. Interestingly, the figure also shows the different speed ratios between engine and vehicle due to the six available gears, and the driver's car mode of use (e.g., the driver often reaches higher revs in fourth gear).  
Conversely, Figure 4 shows the standard deviation of the throttle position versus the average vehicle speed. The higher density of red points at the top of the figure suggests that a rapid variation of the throttle position is more prone to bring to unsafe conditions when the vehicle speed is high. This is probably due to the fact that, when the vehicle is traveling at high speeds, a rapid decrease or increase in the throttle pressure can be the consequence of rapidly changing driving conditions; for example, take the sudden need to brake by quickly lifting the foot off the accelerator in case of danger.  
The standard deviation of the engine load plotted versus the average vehicle speed is reported in Figure 5. Similarly to what has been shown for the throttle position, it seems that at high variation on the engine load corresponds to higher probability of unsafe driving when the vehicle speed is higher.  
**Motion sensors' features:** Motion signals accurately describe the motion of the vehicle which is the result of the driver's actions on the car controls. In particular, they bring basic information about yaw, pitch, and roll of the vehicle which are fundamental to characterizing the driving behavior. Figure 6a-c shows the standard deviation of the angular velocity versus the vehicle speed, measured by the gyroscope, respectively, around the \(x\), \(y\), and z axes. In all three cases, unsafe behaviors are more frequently associated to the points corresponding at high values of the standard deviation together with high values of the vehicle speed. Since the tree axes directly report pitch, roll, and yaw, it is evident that high variations in these quantities, when traveling at high speed, can easily suggest some unsafe behaviors.  
The same trend can be seen in the features calculated starting from the magnetometer signals (Figure 6d-f). In particular, as described in Section 3.2, the x and \(y\) axes together can capture information related to pitch, roll, and yaw. Less evident is the separation between safe and unsafe points for the feature calculated over the \(z\) axis, as it contains only a singular component of the car pitch.  
Figure 4: Scatter plot of the standard deviation of the throttle position versus the average vehicle speed.  
Figure 3: Scatter plot of the maximum value of the engine rotation speed versus the maximum value of the vehicle speed.  
Figure 5: Scatter plot of the standard deviation of the engine load plotted versus the average vehicle speed.  
Figure 6: _Cont._