## 5 Conclusions and Prospects  
In this study, a novel framework was established to implement a systematic evaluation of the lateral stability of the vehicle by considering various impact factors. The software Carsim was utilized to perform simulations. Targeted indicators were adopted to evaluate the effects of seven factors on the lateral stability of the vehicle, including LA, SA, LTR, and \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Parameters of Entropy** & \multicolumn{2}{c}{**Sideslip Stability**} & \multicolumn{2}{c}{**Roll-Over Stability**} \\ \cline{2-5}
**Weight Method** & **LA** & **SA** & **LTR** & **RA** \\ \hline Entropy (\(\omega\)) & 0.9569 & 0.9307 & 0.9480 & 0.9257 \\ Entropy weight (\(\omega\)) & 0.1806 & 0.2904 & 0.2179 & 0.3112 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Entropy weight of each indicator. Figure 14: The impact of driving speed, rutting, road alignment, and adverse weather on CRG. RA, as well as the comprehensive relation grade (CRG). The most important findings of the present study are concluded below:  
1. Four targeted indicators generally experienced several stages, due to the composite effect of lateral wind, rutting, and curve driving, including a stable increasing stage, sharp increase, sharp decrease, and fluctuation. The sharp fluctuation, up and down, of four indicators was due to the process of the wheel driving into a rut and then out of a rut during the lane change. Lateral wind created a relatively weak influence on the indicators' tendencies during the stable increasing stage. 2. LTRs were generally within the threshold, while the maximum RA far exceeded the threshold in the results of single-factor analysis, despite the fact that they both characterized the roll-over stability of the vehicle. Consequently, the application of a single indicator showed limitations in evaluating the lateral stability of the vehicle, so a comprehensive indicator was expected to enhance this defect. 3. The targeted indicators suddenly changed in a short time, due to the wandering behavior caused by rutting. Especially, this sudden change phenomenon was greatly enlarged in the case of WHR = 5. The indicator RA exceeded the threshold after driving across the rutting immediately, i.e., behaving with high driving risks. So, the instantaneous state of crossing severe rutting could be defined as a dangerous moment, which shall be cautiously prevented from the perspectives of both pavement and vehicle. 4. The vehicle was out of control, due to the joint adverse conditions with severe rutting, poor road alignment, strong wind, and low skid resistance, obviously presenting high roll-over risks. Controlling a single factor was unable to ensure driving safety, due to the notable significance of the other factors. The combined requirement of WHR > 10 and \(f>0.4\) was recommended to control the pavement condition for ensuring driving safety in this study. 5. LA and SA had a strong correlation to jointly evaluate the sideslip stability of the vehicle. However, the Pearson's correlation between LTR and RA was small, so a single indicator is weak in performing good efficiency on the roll-over stability of the vehicle. A comprehensive indicator remains to be proposed to enhance evaluation efficiency. 6. A comprehensive relational grade (CRG) was, thus, proposed in the developed framework to improve evaluation performance, and it revealed that vehicle speed and the WHR of rutting had leading effects on driving safety, followed by radius of circular curve, superelevation, crosswind angle, crosswind speed, and friction coefficient, respectively. The findings of this study revealed that the established framework performs well on evaluating the effect of different impact factors on the lateral stability of the vehicle, while driving across rutting, and particularly provides guidance to control pavement conditions from the perspective of driving safety. Despite the aforementioned contributions, a few shortcomings of this study remain to be optimized and enhanced.