# Path Planning Strategy for Vehicle Navigation Based on User Habits
## 3 Results
### Real Routine Verification
#### 3.2.1 Validation of Multi-Index Synchronization Performance Evaluation Model  
(1) Establishment of road performance standards  
To test the accuracy of the road performance quantification system, we first refer to prior examples and existing _city road engineering design standards_, _city road network planning index systems_, _Changsha \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Road Number** & **Standard Road Performance Vector (\(\mathbf{\mathbf{\mathbf{\mathbf{\mathbf{\mathbf{\mathbf{\mathbf{\mathbf{\mathbf{\mathbf{ \mathbf{\mathbf{\mathbf{\mathbf{\mathbf{\mathbf{\mathbf{   }}}}}}}}}}}}}\))** & **Personal-Value \(\omega\)** \\ \hline \multirow{4}{*}{1–12} & [0.77,0.50,0.45] & [0.34,0.74,0.38] & [0.56,0.69,0.72] & 0.62,0.46,0.57 \\  & [0.49,0.59,0.21] & [0.73,0.69,0.66] & [0.66,0.60,0.78] & 0.49,0.67,0.59 \\  & [0.47,0.41,0.79] & [0.21,0.37,0.67] & [0.69,0.60,0.40,46] & 0.42,0.20,0.54 \\  & [0.47,0.52,0.50] & [0.57,0.64,0.33] & [0.68,0.39,0.59] & 0.45,0.55,0.502, \\ \hline \multirow{4}{*}{13–24} & [0.75,0.70,0.39] & [0.64,0.54,0.78] & [0.31,0.42,0.64] & 0.68,0.56,0.33 \\  & [0.44,0.62,0.41] & [0.76,0.53,0.65] & [0.75,0.47,0.36] & 0.48,0.62,0.59 \\  & [0.45,0.62,0.64] & [0.74,0.57,0.79] & [0.23,0.68,0.61] & 0.48,0.62,0.38 \\  & [0.41,0.77,0.33] & [0.69,0.51,0.70] & [0.21,0.73,0.58] & 0.52,0.58,0.38 \\ \hline \multirow{4}{*}{25–36} & [0.28,0.30,28] & [0.32,0.79,0.32] & [0.32,0.36,0.56] & 0.27,0.47,0.31 \\  & [0.56,0.35,0.38] & [0.36,0.73,0.42] & [0.32,0.64,0.55] & 0.44,0.47,0.42 \\  & [0.21,0.25,0.31] & [0.41,0.65,0.21] & [0.43,0.47,0.42] & 0.22,0.44,0.53 \\  & [0.76,0.32,0.39] & [0.48,0.38,0.21] & [0.45,0.60,0.43] & 0.54,0.41,0.47 \\ \hline \multirow{4}{*}{37–48} & [0.71,0.37,0.61] & [0.52,0.48,0.26] & [0.32,0.24,0.22] & 0.53,0.47,0.27 \\  & [0.60,0.79,0.57] & [0.70,0.55,0.57] & [0.21,0.45,0.21] & 0.63,0.60,0.29 \\  & [0.61,0.51,0.21] & [0.43,0.43,0.31] & [0.70,0.46,0.58] & 0.53,0.39,0.95 \\  & [0.50,0.43,0.23] & [0.63,0.55,0.42] & [0.46,0.66,0.50] & 0.41,0.55,0.50 \\ \hline \multirow{4}{*}{49–60} & [0.38,0.52,0.63] & [0.31,0.58,0.62] & [0.32,0.33,0.25] & 0.41,0.39,0.30 \\  & [0.61,0.43,0.47] & [0.38,0.67,0.47] & [0.53,0.61,0.41] & 0.50,46,0.52 \\  & [0.29,0.48,0.29] & [0.62,0.54,0.61] & [0.43,0.68,0.62] & 0.34,0.55,0.49 \\  & [0.72,0.24,0.64] & [0.27,0.56,0.49] & [0.56,0.23,0.53] & 0.49,0.61,0.40 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Personalized performance quantification. Figure 8: Comparison of simulation effect. city traffic planning, Green Plan, and other Changsha cases. Then, we integrate the examples and the actual characteristics of road networks, as well as the results of the Baidu map app and field survey. Subsequently, we develop quantitative descriptions of the selected road network density, road saturation, road quality, environmental quality, speed and economic consumption of six representative variables of road performance to establish road performance standards. In view of the actual complexity of traffic networks, we refer to the path in the city planning classification results and the grade of expansion according to the requirement of this research. The actual performance of road networks that is classified and described is shown in Table 7, along with the actual performance of each road grade. To compare path performances easily, we perform the normalization operation after the data association process to unify the quantitative standard. In view of the high correlation between road time performance and user driving speed, we describe the time performance of the road in interval form. The performance standards of time, economy, and comfort obtained by normalization are shown in Table 8, where T, M, and C represent the time, economic, and comfort values, respectively. (2) Evaluation model verification  
To facilitate the classification, marking and quantification of roads, we establish a simplified road network model based on path guidance in Changsha. We also conduct the process of road quantification and path planning based on the model.