## 2 UAV-Enabled ITS Framework
### First Layer: Technical Specifications
#### 2.1.2 Architectural View  
Utilizing UAVs in an intelligent traffic management system can offer substantial benefits, including broader area coverage, greater flexibility, and improved cost-efficiency compared to traditional ground-mounted solutions [13]. However, several factors must be considered when deploying UAVs optimally for successful traffic monitoring and data acquisition. This subsection will discuss recent developments in modeling and solving UAV deployment challenges. In UAV-enabled ITSs, the architectural view of deployment strategies and trajectory optimization are closely interrelated [26]. Effective deployment strategies rely on optimized trajectories to achieve mission objectives efficiently. Deployment strategies involve the broader planning of where and how to position UAVs for various missions, considering logistical and operational considerations. In contrast, trajectory optimization focuses on refining the specific flight paths of UAVs to enhance efficiency, safety, and task performance. Table 1 summarizes recent research progress on UAV deployment and trajectory optimization. UAV-enabled networks are often quite dynamic due to the ever-changing location of UAV nodes. The dynamicity of UAV networks offers many advantages while aiding the ITS, including improved coverage, the ability to keep pace with the on-road vehicles \begin{table}
\begin{tabular}{c c c c} \hline \hline
**References** & **Research Area** & **Methodology** & **Findings** \\ \hline \multirow{3}{*}{[PERSON] et al. [26]} & Deployment and trajectory optimization of multiple UAVs & \multirow{3}{*}{Quantization theory} & The optimal UAV locations are found to minimize the average power consumption or maximize the data rate of GIs. \\ \hline \multirow{3}{*}{[PERSON] et al. [27]} & \multirow{3}{*}{Quadrotor trajectory tracking} & Filtered observer-based & Able to guarantee a near-zero \\  & & IDA-PBC strategy & steady-state error in situational \\  & & & uncertainties and disturbances. \\ \hline \multirow{2}{*}{[PERSON] et al. [28]} & Multi-objective & Reinforcement & The number of UAVs is minimized for \\  & deployment optimization & learning-based approach & an efficient deployment scheme. \\ \hline \multirow{3}{*}{[PERSON] and [PERSON] [29]} & UAV deployment and & \multirow{3}{*}{Networked swarm model} & The proposed swarm movement is as \\  & network topology & & fast as single UAVs for reaching the \\  & & & destination location. \\ \hline \multirow{2}{*}{[PERSON] and [PERSON] [30]} & \multirow{2}{*}{Emergency UAV deployment} & Optimal deployment algorithm to \\  & & balance UAVs’ diverse flying speeds \\  & & and coverage & \\ \hline \multirow{2}{*}{[PERSON] et al. [31]} & Energy-efficient UAV deployment & \multirow{2}{*}{Deployment model for} \\  & & multi-UAV coverage \\ \hline \multirow{2}{*}{[PERSON] et al. [32]} & Deployment for demand coverage & Centralized deployment algorithm and \\  & & distributed motion control algorithm \\ \hline \multirow{2}{*}{[PERSON] et al. [33]} & \multirow{2}{*}{UAV deployment and communication} & \multirow{2}{*}{Adaptive deployment scheme} \\  & & & displacement and distance. \\ \hline \multirow{2}{*}{[PERSON] et al. [34]} & \multirow{2}{*}{Deployment and movement} & Experience-driven dynamic movement \\  & & and deployment \\ \hline \multirow{2}{*}{[PERSON] et al. [35]} & \multirow{2}{*}{Deployment for IoT} & Both deployment and transmission \\  & & power of UAVs are optimized \\ \hline \multirow{2}{*}{[PERSON] and [PERSON] [36]} & \multirow{2}{*}{UAV deployment} & 3D multi-UAV deployment approach \\  & & & throughput is maximized. \\ \hline \multirow{2}{*}{[PERSON] et al. [37]} & \multirow{2}{*}{UAV network deployment} & \multirow{2}{*}{A decentralized navigation scheme} \\  & & & Enable the UAV to have better views of \\  & & & the ground vehicles by finding the \\ \hline \multirow{6}{*}{Note: GTs = Ground Terminals, IDA-PBC = Interconnection and Damping Assignment-Passivity Based Control, 3D = Three Dimensional, IoT = Internet of Things.} \\ \end{tabular}
\end{table}