## 5 Experimental Analysis
### Preparation of Experimental Data
Drones are launched from designated points along the truck routes to fulfill delivery tasks to these invalid nodes, subsequently rejoining the truck at the next designated point on the route. This approach establishes an efficient parallel delivery system. From the perspective of spatial distribution, the truck routes generated by the algorithm exhibit a strong spatial continuity and balanced coverage. The algorithm endeavors to minimize route intersections and repeated visits, thereby reducing ineffective driving distances to the greatest extent possible. Additionally, the drone routes are designed to complement the truck routes, demonstrating delivery flexibility and effectively covering inaccessible nodes that the trucks cannot reach. In terms of demand coverage, this algorithm achieves an almost complete node coverage rate, with approximately 10 invalid nodes, which is significantly superior to the conventional single-mode delivery method. A quantitative analysis reveals that the total length of the truck route is 33,601 m, while the total flight distance of the drones is 3788 m. Notably, for invalid nodes, the traditional method may necessitate the use of high-cost specialized vehicles or manual delivery. In contrast, this algorithm employs drone collaborative delivery, which not only reduces delivery costs, but also markedly enhances delivery efficiency. Furthermore, the results of the route planning indicate that this algorithm demonstrates a high degree of adaptability in addressing delivery demands across various density regions. In areas characterized by a high demand density, the truck routes are more condensed, thereby optimizing delivery efficiency per unit distance. Conversely, in regions with a low demand density, the collaborative function of drones becomes more significant, effectively compensating for the limitations associated with truck-based delivery. Figure 8 illustrates the benchmark delivery path outcomes in the absence of failed nodes within the road network. It is evident that, in the event of road network failures,  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Distribution Center** & **Distribution Route** & **Route Information** \\ \hline \multirow{4}{*}{Center 1 (Node number 32)} & Route 1 & Truck route: \(32\to 15\to 14-31\to 30\to 2-1\to 33\to 46\to 47\to 34\to 30\to 32\) \\  & Route 1 & Drone route: \(14\to 3\to 30\) \\ \cline{2-3}  & & & \\ \cline{2-3}  & Route 2 & Truck route: \(32\to 36\to 35\to 48\to 49\to 62\to 61\to 60\to 70\to 71\to 72\to 49\to 50\to 51\to 52\to 38\) \\  & & & \\ \cline{2-3}  & Route 3 & Truck route: \(32\to 4\to 5\to 6\to 7\to 17\to 16\to 25\to 24\to 37\to 36\to 32\) \\ \hline \multirow{4}{*}{Center 2 (Node number 57)} & & Truck path: \(57\to 43\to 22\to 28\to 41\to 40\to 39\to 26\) \\  & & \(\to 17\to 18\to 19\to 9\to 10\to 20\to 21\to 11\to 12\to 13\to 11\to 43\to 57\) \\  & Route 1 & Drone path: \(17\to 8\to 27\) \\  & & \(11\to 22\to 23\) \\  & & \(22\to 23\to 13\) \\  & & \(8\to 27\to 19\) \\ \cline{2-3}  & & Truck path: \(57\to 56\to 55\to 65\to 64\to 63\to 53\to 76\to 77\) \\  & Route 2 & \(\to 78\to 88\to 89\to 97\to 98\to 111\to 90 nodes that were previously inaccessible to trucks can be reached by drones. The robust throughput capacity of drones facilitates the overall accessibility of deliveries.