# Reservation-Based 3D Intersection Traffic Control System for Autonomous Unmanned Aerial Vehicles
## 1 Introduction  
UAVs have been gaining interest due to their applications in various areas such as weather monitoring, law enforcement, agriculture, search and rescue, and communication networks [1; 2]. The increasing use of UAVs calls for a system that will ensure safety and efficiency in the airspace [3]. Some laws and regulations for the Unmanned Aircraft System Traffic Management (UTM) framework have been established to improve the safety, security, and efficiency of small UAVs [4]. In the ground transportation system, rules and conventions such as roads, stop signs, traffic signals, intersections, etc. are implemented to provide a proper level of organization to various vehicles. Inspired by this, we proposed an intersection structure in the sky where multiple UAVs can travel across an intersection safely. Our work can be used on applications that require the use of quadcopters such as delivery, surveillance, search and rescue, etc. The scope of our system includes the management of the UAVs' flights from when they approach until they exit the intersection. The UAVs are instructed to follow given rules to be able to travel the intersection safely. The paths of the UAVs in the intersection are centrally managed and cooperatively planned. An intersection manager plans the paths and entrance times of the UAVs in the intersection. Genetic algorithm and modified A* search are used to plan the paths of the UAVs that will minimize their travel times. A reservation-based scheduling approach is used to find the collision-free path in the intersection. The study in [5] introduced the reservation-based scheduling approach to ensure safety in the intersection, which we applied in our scheduling scheme. In [5], the intersection isdivided into multiple sections called cells. When a vehicle travels along the intersection, it will occupy certain cells for a certain time. To avoid collision among the vehicles in the intersection, a cell can be reserved to only one vehicle at a time. There is an intersection manager that has complete information on the reservations of every cell. Before a vehicle enters the intersection, it will send its request to occupy some cells in the intersection to the intersection manager. The intersection manager will check the cells and times they are requested to be occupied and will make the reservation. In our proposed scheme, the intersection space is divided into 3D sections called cubes, and the UAVs reserve the cubes. Our contribution in this work is that we devised a 3D intersection traffic management system to regulate multiple small autonomous quadcopter-type UAVs in shared airspace. To the best of our knowledge, there is no other proposed 3D intersection traffic management systems for autonomous UAVs with the same system model as ours. In particular, we designed a system model that describes the intersection area. We devised a scheme to guarantee that there will be no collisions among UAVs while they approach the intersection. We defined the allowed movements of the UAVs in the 3D intersection. To guarantee collision avoidance in the intersection, we implement the reservation-based scheduling introduced in [5]. We used Genetic algorithm to optimize the scheduling sequence. Since there are multiple possible paths in the intersection across different layers, path-finding is used to find the fastest path in the intersection. In our path-finding implementation, already checked nodes sometimes need to be checked again later. So, we developed a new path-finding algorithm based on the A* search and applied it to our scheduling algorithm.