No abstract

(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Abstract-This paper proposes a taxonomy of Conflict Detection and Resolution (CD&R) approaches for Unmanned Aerial Vehicles (UAV) operation in an integrated airspace. Possible approaches for UAVs are surveyed and broken down based on their types of surveillance, coordination, maneuver, and autonomy. The factors are combined back selectively, with regard to their feasibility for operation in an integrated airspace, into several 'generic approaches' that form the CD&R taxonomy. These generic approaches are then attributed to a number of available method in the literature to determined their position in the overall CD&R scheme. The attribution shows that many proposed methods are actually unsuitable for operation in an integrated airspace. Furthermore, some part of the taxonomy does not have an adequate representative in the literature, suggesting the need to concentrate UAV CD&R research more in those particular parts. Finally, a multi-layered CD&R architecture is built from the taxonomy, implementing the concept of defense-in-depth to ensure UAVs safe operation in an integrated civil airspace.

This paper proposes a novel avoidance method called the Three-Dimensional Velocity Obstacle (3DVO) method. The method is designed for Unmanned Aerial Vehicle (UAV) applications, in particular to autonomously handle uncoordinated multiple encounters in an integrated airspace, by exploiting the limited space in a three-dimensional manner. The method is a three-dimensional extension of the Velocity Obstacle method that can reactively generate an avoidance maneuver by changing the vehicle velocity vector based on the encounter geometry. Adverse maneuvers of the obstacle are anticipated by introducing the concept of a buffer velocity set, which ensures that the ownship will diverge with sufficient space in case of sudden imminence. A three-dimensional resolution is generated by choosing the right plane for avoidance, in which the UAV conducts a pure turning maneuver. Implementation of the 3DVO method is tested in several simulations that demonstrate its capability to resolve various three-dimensional conflicts. A validation using Monte Carlo simulations is also conducted in stressful super-conflict scenarios, which results in zero collisions occurrences for the entire 25,000 samples. Nomenclature BV Buffer Velocity set CC Collision Cone set P φ Avoidance Plane at the angle φ RV i Obstacle Reachable Velocity set S pz Protected Zone VO P φ Velocity Obstacle section on Avoidance Plane-φ VO Velocity Obstacle set α vo Opening angle of the Velocity Obstacle Cone, [-] ∆t Time-step of the VO set generation, [s] δ P Dihedral angle of the avoidance-plane from the XY-plane, [-] ω a.cr Critical avoidance turning rate, [-/s] ω avo Avoidance turning rate, [-/s] φ P Angle of Avoidance Plane around X-axis ψ oi Azimuth angle of the obstacle-i from the ownship, [-] σ col Standard Distribution of Collision Probability, [-] θ oi Elevation angle of the obstacle-i from the ownship, [-] A vo Apex position of the Velocity Obstacle cone, [m] D vo Velocity Obstacle cone symmetric axis vector, [m] E φ vo Escaping point of a VO set, [m/s]

No abstract

No abstract