# A Path Recommendation Method Considering Individual Driving Preferences
## 5 Case Studies
### Results and Analysis of Mid-Trip Secondary Recommendations  
Considering that the traffic conditions in a road network might change, it may become necessary to provide drivers with secondary path recommendations while they are already  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**Maximum Satisfaction Path**} & \multicolumn{3}{c}{**Shortest Length Path**} & \multicolumn{3}{c}{**Satisfaction**} \\ \cline{2-10}  & **Maximum** & **Average** & **Trip** & **Satisfaction** & **Maximum** & **Average** & **Trip Time** & **Satisfaction** & **Difference** \\  & **Density** & **Density** & **Time** & **Density** & **Density** & **Time** & **Satisfaction** & **Difference** \\ \hline
00:00:00 & 3.22 & 1.18 & 463.76 & 75.53 & 3.22 & 1.18 & 463.76 & 75.53 & 0.00\% \\
01:00:00 & 2.68 & 0.88 & 592  
en route. Figure 12 exemplifies this scenario, taking Path 1 as an example, where drivers were offered secondary path recommendations. As node 4819 experienced significant daily traffic flow, the secondary path recommendation focused on its upstream node (node 4879). Prior to reaching node 4879, the new starting point was set at this node, while keeping the end node unchanged. Separate calculations were then performed to assess the path satisfaction from node 4879 to the end of the originally planned path and for the satisfaction with the newly recommended path. Table 25 presents some of the secondary path recommendation results, where \"Change in Satisfaction\" denotes the variation in the satisfaction compared to the actual path. The path numbers in the table correspond to those indicated in Figure 12.  
The above graphs illustrate selected results for secondary path recommendations from node 5122 and at node 4879 during the time period of 7:00-9:00 on a single day. Based on Equation (30), the chosen threshold for secondary path recommendations in this study was 10%. Therefore, among drivers e, f, and g, only driver e received a secondary path recommendation, resulting in a 42.17% increase in satisfaction. It is worth noting that, for this driver, among the underlying index factors--including path travel time (0.103), path length (0.133), number of path lanes (0.148), path turning coefficient (0.127), number of path intersections (0.128), average path density (0.102), maximum path density (0.115), and historical path similarity (0.144)--historical path similarity carried the highest weight  
Figure 12: Path diagram of Path 1, 7, 8, 9 and 10. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Driver**} & \multicolumn{3}{c}{**Original Plan**} & \multicolumn{3}{c}{**Actual**} & \multicolumn{3}{c}{**Secondary Recommendation**} & \multicolumn{1}{c}{**Change in**} \\ \cline{2-11}  & **Path** & **Time** & **Satisfaction** & **Path** & **Time** & **Satisfaction** & **Path** & **Time** & **Satisfaction** & **Satisfaction** \\ \hline e & 7 & 7:43 & 33.13 & 7 & 7:43 & 33.13 & 8 & 7:43 & 47.10 & +42.17\% \\ f & 9 & 8:00 & 41.02 & 9 & 7:58 & 42.73 & 8 & 7:58 & 43.71 & +2.29\% \\ g & 10 & 7:26 & 50.39 & 10 & 7:24 & 48.73 & 8 & 7:24 & 52.06 & +6.83\% \\ \hline \hline \end{tabular}
\end{table} 
Table 25: Comparison of satisfaction using original vs. secondary recommendations. and exerted the most significant influence on the driver. The new suggested path was entirely different from the original path, with a similarity _value_ of 0. Normally, a completely different path should not be recommended. However, through numerical calculations and analysis, it was found that the new path (Path 5) exhibited a significant decrease in maximum path density when compared to the original planned path (Path 7), as well as a lower number of intersections, resulting in a substantial increase in satisfaction. This result demonstrates the necessity and feasibility of quantitative analysis of these indicators. The above figure showcases only part of the recommendation results.