## 4 Field Experiment Evaluations
### Collision-Avoidance Experiment Evaluations  
To evaluate the avoidance effect caused by Algorithm 1 implemented in our proposed AFCCS, similar to our previous study in [27], for arbitrary UAV\({}_{n}\), we define a parameter \(\gamma_{n,k}\), which means the intrusion distance of UAV\({}_{k}\) to UAV\({}_{n}\) and can be calculated by  
\[\gamma_{n,k}=\max\bigl{(}r_{n,k}+r_{n,n}-\big{|}\big{|}(x_{n,n},y_{n,t},z_{n,n })-(x_{n,k},y_{n,k},z_{n,k})\big{|}\big{|}_{2},0\bigr{)}. \tag{11}\]  
From (11), it can be known that the intrusion distance \(\gamma_{n,k}\) ranges from 0 to \(r_{n,k}+r_{n,n}\), and a collision between UAV\({}_{n}\) and UAV\({}_{k}\) occurs when \(\gamma_{n,k}=r_{n,k}+r_{n,n}\). The risk of collision between two UAVs decreases with a decrease in \(\gamma_{n,k}\). An experimental result of UAVs before, during, and after the detected collision event in the field experiment is shown in Figure 12. This type of visualization is created by generating flight paths through the creation of KML files using latitude and longitude data acquired during experiments for each UAV, and subsequently plotting these paths on Google Earth. In Figure 12, \(N=4\) UAVs were positioned at the top corners of a square area and flown towards their destinations in a diagonal direction. The flight paths of all the UAVs and the intrusion distance of each UAV are recorded for analysis of the collision avoidance. Figures 13 and 14 present the intrusion distances over time for the collision-avoidance experiments with different flight patterns. In the first experiment, the Drone Mapper in our developed AFCCS utilizes a LoRa wireless module with an information-sharing duration of \(T=0.5\,\mathrm{s}\) and a fixed speed of \(2\,\mathrm{m}/\mathrm{s}\) for all UAVs \(v_{n,n}\,\forall\,n\in\{1,\cdots,N\}\), which represents \begin{table}
\begin{tabular}{l r} \hline \hline
**Parameter** & **Value** \\ \hline Experiment Environment & Open airspace in suburb \\ \hline Communication Protocol & LoRa or FSK \\ \hline Number of UAVs, \(N\) & 2 or 4 \\ \hline Alert radius, \(r_{n,n}\)/\(n\) & 10 m or 15 m \\ \hline Speed, \(v_{n,n}\)/\(v_{n}\) & 2 m/s or 5 m/s or 6 m/s \\ \hline Information-sharing duration, \(T\) & 0.5 s or 0.25 s \\ \hline Distance between leader and follower, \(D\) & 10 m \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Experimental parameters. \begin{table}
\begin{tabular}{l r} \hline \hline
**Parameter** & **Value** \\ \hline Model & UAV-E6106 FA2 \\ \hline Serial Number & F2000016 \\ \hline Registration Code & JU32263 EB76X \\ \hline Weight & 8.32 kg \\ \hline Dimensions & 1060 mm (diagonally between motors) \\ \hline Flight Time & approximately 30 min \\ \hline Maximum Payload & approximately 6.2 kg \\ \hline Maximum Flight Speed & 72 km/h \\ \hline Wind Resistance & 10 m/s \\ \hline \hline \end{tabular}
\end{table} 
Table 3: UAV specifications. a low-speed flight pattern. In this case, the alert radius \(r_{n,n}\) of UAV\({}_{n}\) is set to 10 m for all \(n\in\{1,\cdots,N\}\). On the other hand, the second experiment employs the FSK wireless module in the AFCCS, with an information-sharing duration of \(T=0.25\) s and a fixed speed of 5 m/s for all UAVs \(v_{n,n}\)\(\forall\,n\in\{1,\cdots,N\}\), which represents a high-speed flight pattern. In this case, the alert radius \(r_{n,n}\) of UAV\({}_{n}\) is set to 15 m for safety considerations. From Figures 13 and 14, it can be seen that all intrusion distances for the UAVs throughout the observation period are below the theoretical maximum of \(r_{n,n}+r_{n,k}\) (20 m for the first experiment and 30 m for the second experiment) when using the proposed collision-avoidance algorithm. This means that the UAVs can safely arrive at their destinations without colliding with each other, showing the effectiveness of the proposed AFCCS for collision avoidance during UAV flights. However, in comparison to the low-speed flight pattern with \(v_{n,n}=2\) m/s, the high-speed flight pattern with \(v_{n,n}=5\) m/s appears to have more safety risks.