## 4 Experimental Results and Analysis
### Experimental Result
#### 4.2.3 Sensitivity Analysis of Algorithm to Urgency  
To verify that the algorithm in this paper can plan different travel routes according to different urgency levels, three urgency degrees were selected, namely, \(urgency=0.2\), \(urgency=0.5\), and \(urgency=0.8\). The travel time, quality ratio, scenic score, and running time were tested on the Xi'an and Wuhan road network datasets (departure time \(t_{0}=9\):\(00\)). The average results are shown in Figure 10. Figure 10 shows that for different urgencies, the travel time of the fastest algorithm is always the same and the shortest because the fastest algorithm plans the shortest path between two points and is not affected by urgencies. When \(urgency=0.2\), the improved GA aims to plan the route with the highest scenic score for users. It can search more edges with high scenic scores, so the travel time is slightly higher than that of the MA and the traditional GA. When \(urgency=0.5\), the goal of the improved GA is to plan a route with a high-quality ratio for users, taking into account both the scenic score and travel time of the edges. Therefore, the travel time is lower than that of the MA. When \(urgency=0.8\), the improved GA and the traditional GA aim to plan the shortest travel time route for users, however, due to the weak search ability of traditional GA, the travel time is high. The MA is still used to plan the scenery route meeting time constraints for users. Therefore, the travel time of the improved GA is close to that of the fastest algorithm, while that of the MA is the highest. The comparison results of the path quality ratio under different urgencies are shown in Figure 11. In Figure 11, for different urgencies, the quality ratio of the fastest algorithm is always the same and the lowest. When \(urgency=0.2\), the quality ratio of the MA is the highest because in this case, the improved GA will add more scenic edges to the path to maximize the scenic score of the path. The quality ratio of the improved GA is better than that of the traditional GA, because the gene replacement operator improves the search ability of the GA. When \(urgency=0.5\), the improved GA can maximize the quality ratio of the path, so the quality ratio is the highest. When \(urgency=0.8\), the quality ratios of several algorithms are close because there is not enough time budget to search for higher quality edges. Figure 9: Comparison of the running time of the algorithm under different start end pairs. (**a**) Xi’an; (**b**) Wuhan. The comparison results of the scenic path score under different urgencies are shown in Figure 12. For different urgencies, the scenic score of the fastest algorithm is always the same and the minimum. When \(urgency=0.2\), the scenic score of the improved GA is the highest because when it is not urgent, the goal of the improved GA is to maximize the scenic score of the path, and compared with the MA and the traditional genetic, it can search more and better scenic edges. When \(urgency=0.5\), although the goal of the improved GA is to maximize the quality ratio of the path, the path scenic score is still the largest. When \(urgency=0.8\), the scenic score of the improved GA is close to that of the fastest algorithm and slightly lower than that of the MA. The reason for this result is that the MA still chooses the scenic edge when encoding chromosomes, and the running time and travel time of the algorithm will be relatively high. The scenic score of the traditional GA is slightly higher than that of the improved GA, because although the traditional GA also plans the fastest route for users at this time, its search ability is weaker than that of the improved GA, so the path travel time is higher. Finally, the comparison results of the algorithm running time under different urgencies are shown in Figure 13. For different urgencies, the running time of the fastest algorithm is the same and always the shortest. With \(urgency=0.2\) and \(urgency=0.5\), the running time of the improved GA is slightly lower than that of the MA for two reasons.