## 4 Results
### User Study
#### 4.2.1 Regression Analysis  
A regression analysis using the modified Stevens's power law returns the following results for the investigated maneuvers. For Maneuver A, the objective value jerk onset with R\({}^{2}\) = 0.7073 shows the highest goodness-of-fit (Table 3). The second highest goodness-of-fit is achieved by the objective value longitudinal jerk on the throttle, with R\({}^{2}\) = 0.6786 (Figure 7). This confirms that in addition to transverse jerks, occupants also react sensitively to longitudinal jerks. The objective variables total acceleration and total jerk, intended for simplified evaluation, have an R\({}^{2}\)-value of 0.5996 and 0.6156, respectively. The lowest goodness-of-fit, with R\({}^{2}\) = 0.4701, is with the objective variable jerk in the curve change. One possible reason for this is the distance between the two corners. The distance of 4 m is rather generous so that a clear change of direction may be difficult to identify for the test person. A reduction in the distance can fix this issue. It is noticeable that within the maneuver, the coefficients determined from the regression for similar objectification variables have similar magnitudes. This is an indication that the model used for the regression analysis is correct. The objective variables, lateral acceleration, acceleration jerk, and total acceleration, have a progressive relationship between subjective judgment and the magnitude \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Objective Value** & **R\({}^{2}\)** & **k** & **X\({}_{0}\)** & **n** & **Resulting Formula** \\ \hline Lateral acceleration & 0.6355 & 0.9712 & 2415 & 1182 & \(Y\) = 1 + 0.9712 \(\left(\frac{\mu_{\pi}}{m^{3}}-2415\right)^{182}\) \\ Jerk onset & 0.7073 & 0.9359 & 2196 & 0.6538 & \(Y\) = 1 + 0.9359 \(\left(\frac{\mu_{\pi}}{m^{3}}-2196\right)^{18638}\) \\ Jerk switch & 0.4701 & 0.5918 & 3630 & 0.6922 & \(Y\) = 1 + 0.5918 \(\left(\frac{\mu_{\pi}}{m^{3}}-3630\right)^{0.6922}\) \\ Jerk end & 0.6149 & 0.9122 & 3453 & 0.6202 & \(Y\) = 1 + 0.9122 \(\left(\frac{\mu_{\pi}}{m^{3}}-3453\right)^{0.6802}\) \\ Longitudinal acceleration & 0.5150 & 2100 & 1750 & 0.5939 & \(Y\) = 1 + 2100 \(\left(\frac{\mu_{\pi}}{m^{3}}-1750\right)^{0.5909}\) \\ Jerk on gas & 0.6786 & 0.5270 & 0.8827 & 1239 & \(Y\) = 1 + 0.5270 \(\left(\frac{\mu_{\pi}}{m^{3}}-0.8827\right)^{1229}\) \\ Jerk on brake & 0.5480 & 0.8718 & 1061 & 0.8913 & \(Y\) = 1 + 0.8781 \(\left(\frac{\mu_{\pi}}{m^{3}}-1061\right)^{12}\) \\ Total acceleration & 0.5996 & 1147 & 2628 & 1005 & \(Y\) = 1 + 1147 \(\left(\frac{\mu_{\pi}}{m^{3}}-2628\right)^{1063}\) \\ Total jerk & 0.6156 & 0.5009 & 3879 & 0.7801 & \(Y\) = 1 + 0.5009 \(\left(\frac{\mu_{\pi}}{m^{3}}-3879\right)^{0.7802}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Results from the regression analysis for all objective values in Maneuver A.  
Figure 7: Regression analysis for the objective value longitudinal jerk on gas in Maneuver A.  
of the measured value. For all other objective quantities, there is a degressive relationship. The evaluation thresholds (X\({}_{0}\)) are lower for longitudinal-dynamic objective quantities than for their transverse-dynamic counterparts. This finding is consistent with the comments by Test Persons 2 and 3, who stated that they feel their comfort perception is reduced more by lateral dynamic effects than by longitudinal ones. For Maneuver B, the regression analysis leads to R\({}^{2}\) values of 0.4654 to 0.7557 (Table 4). As with Maneuver A, the objective value jerk onset (Figure 8) achieves the highest goodness-of-fit, with R\({}^{2}\) = 0.7557. This indicates a special significance of the characteristic value for evaluating the comfort of a driving style. One explanation for this is that the jerk onset is less predictable for the occupants due to the partial obstruction of vision and the abruptness of its occurrence.