# Reservation-Based 3D Intersection Traffic Control System for Autonomous Unmanned Aerial Vehicles
## 2 Related Work  
The problem of UAVs' integration into the urban airspace was also addressed in papers in [6; 7; 8; 9]. A framework consisting of a decentralized approach is implemented in [6; 7]. In [8; 9], a structure for the low-altitude airspace com of airways and nodes was proposed, where the UAVs travel along the airways and the airways are connected by the nodes. The UAVs decide which airways to take according to their objectives. The main difference between their approach with ours is that our approach is focused on the intersection level. In their proposal, they assume only one swarm of UAVs, with the same source and destination, can occupy a node at the same time. In our proposal, there can be multiple UAVs, with different sources and destinations, traveling across the intersection at a time. Consequently, there have been many studies on the path-planning of UAVs. Among these studies, the common considerations are collision avoidance, kinematic constraints of the UAVs, and optimization of various criteria such as minimizing the path length and energy or fuel consumption. Collision avoidance is crucial for the safer integration of UAVs in the airspace. A comprehensive survey on recent collision avoidance approaches is in [10]. In this study, collision avoidance techniques are categorized into deliberative and reactive planning. In deliberative planning, a collision-free path is searched for in a known updated map of the environment and the found path is executed while in reactive planning, the UAVs gather information about the surroundings in real-time using sensors, and the UAVs react based on the obtained sensor information. When planning a path in an unknown environment, sampling-based algorithms are used to generate a path from the starting position of the UAV to its destination. In a sampling-based approach, points in the environment are sampled and the points are added to the map if there is a collision-free path between the points [11]. Some of the sampling-based approaches are rapidly exploring random trees [12; 13], probabilistic road map [14; 15], and Voronoi graphs [16]. To consider the feasibility of the paths based on the the swarm formation. A swarm of UAVs was also used in [54]The time is discretized using time interval \(\Delta t\). At every time instant \(t_{j}\) where \(t_{j}-t_{j-1}=\Delta t\), the UAVs on the lane decide the acceleration or deceleration rates that they will respectively use at \(t_{j+1}\), such that they will not collide with a UAV ahead and they will enter the intersection as scheduled, if they are already scheduled. The requests of the UAVs are processed by the intersection manager at every time interval \(k\Delta t\) where \(k\) is some positive integer and the scheduling time instant is synchronized with the discretized time. At scheduling time instant \(t_{i}\), the requests processed by the intersection manager are the requests received at \((t_{i}-k\Delta t,\ t_{i})\). After scheduling, the intersection manager sends responses to the UAVs that sent requests. A response to a UAV includes a UAV's scheduled entrance time to the intersection and the path of the UAV in the intersection. The scheduling and responses to all scheduled UAVs must be completed within \(k\Delta t\). A UAV in the approaching area is expected to follow the following rules:  
* It cannot change lanes
* It cannot overtake a UAV ahead
* It must travel at constant altitude
* It must maintain its speed within \([s_{min},s_{max}]\), unless it needs to slow down to avoid collision with UAV ahead or delay its entrance to the intersection. We will discuss in Section 4 how a UAV will decide its speed such that it can avoid collision with a UAV ahead and enter the intersection as scheduled. * It must send reservation request to the intersection manager as soon as it enters the reservation zone. A reservation request message contains the UAV ID, time the request was sent, UAV's position when it sent the request, UAV's lane, and UAV's size.