# Path Planning Strategy for Vehicle Navigation Based on User Habits
## 3 Results
### Real Routine Verification
#### 3.2.2 Validation of the Effectiveness of Personalized Planning
Moreover, by replacing Wan Jiali viaduct with going around the city at high speed, guaranteeing the time performance, it avoids the extra cost of passing through the road and the distance from the bypass, and improves the economic performance of the path. According to the calculation results related to the time and economic performance and the effective road length in Table 12, the time consumption rates of the red planning path and blue reference path are 57.362 and 68.016, respectively, and the economic losses are 69.576 and 98.252, respectively. In comparison with the reference path, the personalized path that integrates user A's habits shows improved comfort and economic performance. This result is consistent with the driving characteristics of user A, focusing on time and economic performance. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Path Name** & **Related Road** & **Level** & **T** & **M** & **C** & **Personal-Value** & **Effective Length/km** \\ \hline \multirow{6}{*}{Literature Reference Route} & Yun Qi Road & 4 & 0.49 & 0.35 & 0.53 & 0.45 & 3.77 \\  & South Second Ring & 4 & 0.49 & 0.35 & 0.53 & 0.40 & 8.77 \\  & East Second Ring Road & 3 & 0.37 & 0.22 & 0.38 & 0.25 & 8.78 \\  & 31 Avenue & 3 & 0.48 & 0.28 & 0.43 & 0.33 & 1.95 \\  & Wan Jialiali viaduct & 2 & 0.67 & 0.65 & 0.59 & 0.58 & 2.50 \\  & Wan Jiali North Road & 6 & 0.37 & 0.32 & 0.47 & 0.31 & 2.54 \\  & Xianghu West Road & 7 & 0.28 & 0.30 & 0.34 & 0.27 & 1.13 \\ \hline \multicolumn{2}{c}{Log trajectory} & just as same as the personalized path that combines B’s habits} \\ \hline \hline \end{tabular}
\end{table} 
Table 12: _Cont._  
Figure 10: (**a**) The optimal path model for user B; (**b**) The optimal actual planning path for user B. Where, the green represents log trajectory, the blue represents literature Reference resources Route, and the red represents the Individualization Route based on B. Detailed performance of the relevant roads refer to Table 12.  
\(\bullet\) Intra-class validation  
(3) Example 3  
This example is the personalized path planning for time + economic user C ([0.56,0.37,0.07]), and user B's planning path constitutes the intra-class verification of personalized path performance. Users C and B ([0.35,0.57,0.08]) share similar features, belong to the same time + economic type, pay attention to time and economic factors, while ignore the factors of comfort effect. However, there are two different levels of attention in time and economy. C users are more inclined to time, with a level of 1, a coefficient of 0.56, a second economic factor, a level of 2, and a coefficient of 0.37. Reference example A makes personalized path planning from user C's perspective. The personalized performance and effective length of the related roads are shown in Table 13.  
Table 12 shows that the Yun Qi Road, South Second Ring, Wan Jiali viaduct, Wanjiali North Road, and Xianghu West Road also appear in the same type of path planning of users B and C. Path planning is of different types for users A and B. The same type of road users has different personalized performance, particularly for users B and C. With large effective length differences, the amplitude becomes increasingly small. The similarity obviously improves path planning. Path planning at a similar degree increases with the increase of similarity between user feature vectors.