## 2 UAV-Enabled ITS Framework
### Second Layer: Communication Networks for Traffic Monitoring
#### 2.2.2 Advances in Traffic Monitoring
The authors designed a mixed-integer linear programming (MILP) model for the scheduling problem and proposed a local branching-based solution method. The suggested approach could quickly find a better solution while still approximating the actual solution. A Shanghai road traffic case study demonstrated the MILP model's effectiveness and use of the solution method. [PERSON] et al. [6] proposed a UAV-based smart traffic monitoring system to overcome limitations and loopholes. The smart system consists of three layers as follows: the first layer is the monitoring layer, where a UAV equipped with an advanced camera is deployed to monitor highway traffic and detect speed and other traffic violations; the second layer consists of a 5G communication technology, which connects the first layer with the base station; and the third layer consists of highway traffic where the actual violations take place. The proposed intelligent traffic monitoring system helped reduce accidents and fatalities in the projected results. A cooperative traffic monitoring system was proposed to help drivers with surrounding vehicle information by [PERSON] et al. [53]. In this system, traffic images are taken using UAVs and sent as input to a semantic neural network. The neural network provides a segmented vehicle image as output with an attached 2D geographic location. These output data are then sent to other vehicles to inform them about the location of the vehicle on the road. Several experiments have demonstrated that the proposed traffic monitoring system is efficient and robust. [PERSON] and [PERSON] [56] introduced a rapid monitoring system based on UAVs to facilitate emergency response in real time. An integration test was conducted to evaluate the performance of the proposed system. While performing tests, data were acquired from the test site in real time, and by processing the data, a high-quality digital elevation model and orthoimages were generated. However, the usage of UAVs in actual road traffic management is still under investigation [48]. Much research has been conducted to develop autonomous UAV-based traffic monitoring systems. Figure 6 shows an example of a general traffic monitoring scenario using UAVs in coordination with service stations and roadside units (RSUs). [PERSON] et al. [55] originally proposed the Wallenberg Laboratory for Information Technology and Autonomous Systems (WITAS) UAV project, which aimed to successfully develop methods and technologies necessary to operate autonomous UAVs over large-scale transportation networks. The project was multidisciplinary and required many different research competencies. The UAV was designed to have automatic navigation capabilities at various altitudes, including take-off and landing. The UAV was expected to perform multiple vehicle detections, tracking, and parameter extractions to achieve a specific mission goal and to identify complex traffic behaviors, such as vehicle overtaking, traversing of intersections, and parking lot activities. Figure 6: Traffic monitoring scenario using UAVs. Parameter perceptions from operating environments and devising and implementing plans based on these perceptions are essential abilities of an autonomous UAV system. Although many research works have built and implemented plans in their autonomous systems, few efforts have been made to perceive the environmental parameters and devise a plan accordingly. [PERSON] et al. [57] proposed an autonomous system consisting of ground sensors and UAVs to track traffic on a road network. In their proposed system, each UAV can communicate with unattended ground sensors and other UAVs to find traffic of interest. The authors demonstrated autonomous decision-making by conducting field experiments where two UAVs autonomously collaborated to track a moving ground vehicle. To facilitate the development of autonomous UAV systems, [PERSON] et al. [58] introduced an open-source software framework named UxAS for prospective teams of unmanned systems.