## 4 Experimental Results
### Analysis of Results
#### 4.4.2 Experiment 2: Calculation of Indicators' Weights for Traffic Trend Prediction  
The road traffic situation indicators were analyzed by the AHP method, and the weights of the four first-level indicators in the criterion layer were \(W_{U}=[0.072,0.279,0.649]\). According to the criteria of the average randomness indicator in Table 3, the \(CR\) of the criterion layer is \(CR=0.009<0.1\), which satisfies the consistency test. Then, the weights of the indicator layer are calculated. The indicator layer weights--\(W_{U_{1}}\) for the Road Factors \(U_{1}\), \(W_{U_{2}}\) for the Natural Factors \(U_{2}\), and \(W_{U_{3}}\) for the Human Factors \(U_{3}\)--are \(W_{U_{1}}=[0.053,0.106,0.255,0.586]\), \(W_{U_{2}}=[0.263,0.079,0.659]\), and \(W_{U_{3}}=[0.777,0.153,0.070]\). The \(CI\) and \(CR\) of the three indicator layers are less than 0.1 at \(CR_{1}=0.027\), \(CR_{2}=0.009\) and \(CR_{3}=0.009\), which satisfies the consistency test. The results of the weights are shown in Table 9.  
The final AHP method calculates the weights of road traffic trend indicators under emergencies, as shown in Equation (40). \[W_{1}=[0.00381,0.00763,0.01836,0.04219,0.07337,0.02204,0.18386,0.504,0.09930, 0.0454] \tag{40}\]  
Similarly, the results of the objective weights of the indicators determined by the EM method are shown in Table 10. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Guideline Layer \(U\)** &
\begin{tabular}{c} **Guideline Layer** \\ **Weights** \\ \end{tabular} & **Indicator Layer** & **AHP Weights** \\ \hline \multirow{4}{*}{Road Factors \(U_{1}\)} & & \(U_{11}\) & 0.00381 \\  & & \(U_{12}\) & 0.00763 \\  & & \(U_{13}\) & 0.01836 \\  & & \(U_{14}\) & 0.04219 \\ \hline \multirow{4}{*}{Natural Factors \(U_{2}\)} & & \(U_{21}\) & 0.07337 \\  & & \(U_{22}\) & 0.02204 \\  & & \(U_{23}\) & 0.18386 \\ \hline \multirow{4}{*}{Human Factors \(U_{3}\)} & & \(U_{31}\) & 0.504 \\  & & \(U_{32}\) & 0.0993 \\ \cline{1-1}  & & \(U_{33}\) & 0.0454 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: The weighting of road traffic trend indicators for the AHP method. The objective weights of the three first-level indicators in the criterion layer are \([0.524,0.183,0.293]\). The objective weights of the four second-level indicators under the guideline layer of Road Factors \(U_{1}\) are \([0.053,0.080,0.223,0.168]\), the objective weights of the three second-level indicators under the guideline layer of Natural Factors \(U_{2}\) are \([0.060,0.051,0.072]\), and the objective weights of the three second-level indicators under the guideline layer of Human Factors \(U_{3}\) are \([0.073,0.083,0.137]\). The weights calculated by the final EM method are shown in Equation (41). \[W_{2}=[0.053,0.08,0.223,0.168,0.06,0.051,0.072,0.073,0.083,0.137] \tag{41}\]  
The weights of the traffic trend indicators were calculated using the GT-AHP-EM method, and the weighting results are shown in Table 11. The combination coefficients of the AHP and EM weighting methods were \({\alpha_{1}}^{*}=0.6666312219719346\) and \({\alpha_{2}}^{*}=0.3333687780280654\), respectively. The objective weights of the four first-level indicators in the criterion layer were \([0.2225,0.2472,0.5303]\). The final GT-AHP-EM weights are shown in Equation (42). \[W^{*}=[0.0202,0.0317,0.0865,0.0841,0.0689,0.0317,0.1466,0.3605,0.0939,0.0759] \tag{42}\]  
In the road traffic situation assessment model under emergencies, from the weights calculated by the GT-AHP-EM method, the weight of the road section law enforcement officers \((U_{31})\) is the largest. Once an urban road emergency occurs, the road section law enforcement officers can quickly maintain the traffic order of that road and reduce the impact caused by the emergency. The number of law enforcement officers determines the length of time for the road to restore stability, so the traffic management process after urban road emergencies should be carried out in the intersections prone to emergencies with reasonable arrangements of law enforcement officers to do an excellent job of emergency