## 4 Results
### Optimization Analysis of Rest Facility Layout  
Based on the above experimental results, for the FangQiao and LingQiao rest areas where the rest facilities cannot meet the needs of the elderly, we used the GIS spatial analysis method and referred to the resource layout of the scenic area with sufficient rest facilities (Ginkgo Avenue rest area), and carried out the optimization analysis of the layout of the rest facilities in these two areas.  
Through the buffer zone analysis, we generated a service coverage with a radius of 10 m centered on the existing rest facilities and identified the areas within the rest area that were not covered by service facilities, i.e., the service blind zones. On the roads in the service blind zones, one new rest facility point was added every 10 m according to an even distribution. The optimized service facility layout is shown in Figure 11.  
Through the optimized layout, the new leisure facilities effectively covered the original service blind zones and significantly enhanced the service capacity of the rest area. The density of service facilities in FangQiao rest area had increased from 3.5 to 7.5 per 100 m, and the density of service facilities in LingQiao rest area had increased from 1 to 5.5 per 100 m, which could effectively improve the aging-friendly adequacy rate of service facilities and better meet the resting needs of the elderly.  
We employed a quantitative predictive model to assess the improvement in age-friendliness after increasing facility density. Based on current data and assuming constant visitor flow, we used an inverse relationship model to estimate the projected occupancy rate after adjusting facility density. The calculation formula is as follows:  
\[\mathrm{F}^{\prime}=\mathrm{F}\times\left(\mathrm{D}/\mathrm{D}^{\prime}\right) \tag{3}\]  
Figure 11: Optimized layout of scenic service facilities.  
In the formula, F represents the original occupancy rate, F\({}^{\prime}\) represents the new occupancy rate after the change in facility density, D represents the original facility density, and D\({}^{\prime}\) represents the new facility density.  
According to this prediction method, the current service facility density at FangQiao rest area was 3.5 units per hundred meters, with an occupancy rate of 62.50%. At full capacity, the average non-elderly occupancy rate was 91.33%. Based on the aging-friendly adequacy rate evaluation criteria established in this study, its aging-friendly adequacy level was classified as \"relatively low\". If the service facility density was increased to 7.5 units per hundred meters while keeping visitor numbers constant, the occupancy rate was projected to decline to approximately 29.17%. At this point, according to the evaluation criteria (where F \(<\) 30% corresponded to a \"high\" aging-friendly adequacy rate), the rest area's sufficiency level would improve from \"relatively low\" to \"high\". Similarly, LingQiao rest area currently had a service facility density of 1 unit per hundred meters and an occupancy rate of 74.17%, which, according to the evaluation criteria (F \(>\) 70% = \"low\" sufficiency rate), placed it in the \"low\" category. However, if the facility density was significantly increased to 5.5 units per hundred meters (with no change in visitor numbers), the occupancy rate was expected to drop sharply to approximately 13.49%, well below the 30% threshold. Consequently, the rest area's aging-friendly adequacy rate would jump directly from \"low\" to \"high\". These adjustments indicate a substantial increase in seating availability, significantly improving accessibility and convenience for elderly users of rest facilities.