Yazdi I. Jenie

Selective Velocity Obstacle Method for Cooperative Autonomous Collision Avoidance System for Unmanned Aerial Vehicles

Autonomous collision avoidance system (ACAS) for Unmanned Aerial Vehicles (UAVs) is set as a tool to prove that they can achieve the equivalent level of safety, required in context of integrating UAVs flight into the National Airspace System (NAS). This paper focus on the cooperative avoidance part, aiming to define an algorithm that can provide avoidance between cooperative UAVs in general, while still be restricted by some common rules. The algorithm is named the Selective Velocity Obstacle (SVO) method, which is an extension of the Velocity Obstacle method. The algorithm gives guidelines for UAVs to select between three basic modes for avoidance, i.e., to Avoid, Maintain, or Restore. The variation of those three modes gives flexibility for UAVs to choose how will they avoid. By modeling the algorithm as a hybrid system, simulations on various UAVs encounters scenario were conducted and shows satisfying result. Monte Carlo simulations are then conducted to conclude the performance even more. Randomizing the initial parameters, including speed, attitude, positions and avoidance starting point, more than 10 encounter scenario were tested, involving up until five UAVs. A parameter called the Violation Probability is then derived, showing zero violations in the entire encounter samples.

Cooperative Autonomous Collision Avoidance System for Unmanned Aerial Vehicle

Autonomous collision avoidance system (ACAS) was defined and investigated in this paper to support UAVs integration to the national airspace system. This includes not only UAVs on-board system, but also the definition of requirements, collision avoidance structure, and the avoidance rules. This paper focuses on the cooperative avoidance, where UAVs (or any aircraft) involved avoid each other using rules previously agreed by involved parties. A novel algorithm of avoidance was developed, named as Selective Velocity Obstacle (SVO) method. Several simulations were conducted and show satisfying result on how well the algorithm work to avoid separation violations. In the end of the paper, using Monte Carlo simulation, violation probabilities were derived for three setups. These simulations shows the performance of the developed algorithm for cooperative ACAS, and suggesting the need to derive a new parameter, i.e., the minimum required turning rate of avoidance.

Taxonomy of Conflict Detection and Resolution Approaches for Unmanned Aerial Vehicle in an Integrated Airspace

This paper proposes a taxonomy of conflict detection and resolution (CD&R) approaches for operating unmanned aerial vehicles (UAVs) in an integrated airspace. Possible approaches for UAVs are surveyed and broken down based on their types of surveillance, coordination, maneuvering, 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 methods in the literature to determine 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 multilayered CD&R architecture is built from the taxonomy, implementing the concept of defense in depth to ensure safe operation of UAVs in an integrated civil airspace.

Three-Dimensional Velocity Obstacle Method for Uncoordinated Avoidance Maneuvers of Unmanned Aerial Vehicles

This paper proposes a novel avoidance method called the three-dimensional velocity obstacle method. The method is designed for unmanned aerial vehicle 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 unmanned aerial vehicle conducts a pure turning maneuver. Implementation of the three-dimensional velocity obstacle method is tested in several simulations that demonstrate its capability to resol...

Velocity Obstacle Method for Non-cooperative Autonomous Collision Avoidance System for UAVs

Unmanned Aerial Vehicles (UAVs) are required to have Autonomous Collision Avoidance System (ACAS) to resolve conflicts, especially when flying in the National Airspace System (NAS). This paper focused on the non-cooperative concept for avoidance, where UAVs face rogue obstacle that does not cooperatively share their flight data, nor they follows the rule of the air. UAVswill rely on its on-board sensor for avoidance, in space and time range that is limited. The limitation make the entire process of sense, detect, and avoid (SDA) mostly not applicable, and sense and avoid (SA) manner is more preferable and safe. A method called SA-VO that extend the use of the known Velocity Obstacle (VO-) method is introduce to handle the problem. The method produce more efficient avoidance in the non-cooperative space than SA manner of avoidance, without fully run the SDA process. Probability of collision map based on ranges of obstacle range of positions and velocity is predefine to replace the detection part of SDA. The method is then tested using simulations of encounters between UAV and an obstacle. The simulations show that SA-VO can be a middle ground between the SDA and SA manner of avoidance.

Three-dimensional velocity obstacle method for UAV deconflicting maneuvers

Autonomous systems are required in order to enable UAVs to conduct self-separation and collision avoidance, especially for flights within the civil airspace system. A method called the Velocity Obstacle Method can provide the necessary situational awareness for UAVs in a dynamic environment, and can help to generate a deconflicting maneuver.This paper focuses on the assessment of the Velocity Obstacle Method application and its ability to resolve various conflict situations in three dimensional space. This assessment results in a redefinition of the criteria of avoidance. A novel technique is introduced to support the avoidance decision, by representing the conflict situation in various avoidance-planes. Several new definitions to support the method are introduced. This method is then implemented in three-dimensional simulations for UAVs in cases of conflict, in which more than one option of resolution is provided.

Safety Assessment of Unmanned Aerial Vehicle Operations in an Integrated Airspace

This paper focuses on the safety assessment of Unmanned Aerial Vehicles (UAVs) operating in an integrated airspace system. The assessment is based on series of Monte Carlo Simulations to include the effect of the variety of Conflict Detection and Resolution (CD&R) systems in each involved vehicle. The difficulty of using Monte Carlo simulations in the assessment, in which collision are rare to be sufficiently represented, is overcome by the use of a high density airspace with a periodic boundary condition. This setup, along with the randomization of the UAV states and the CD&R parameters, increases the number of conflicts and resolutions for each Monte Carlo sample to rapidly reach convergence. The parameters derived, including the mean ratio of time in which the vehicle are in either mission mode, avoidance mode, or in a Near Mid Air Collision (NMAC) situation, are compared to similar Monte Carlo simulation results where no CD&R system is used. The proposed method is a versatile safety assessment method for various encounter situations a UAV an its CD&R system might face in its operation in an integrated airspace system.

Three-Dimensional Velocity Obstacle Method for UAV's Uncoordinated Avoidance Maneuver

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 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 before the collision. 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 for the entire set of samples.

Hybrid Modeling of Velocity Obstacle Method in Autonomous Collision Avoidance System for Unmanned Aerial Vehicles

This paper presents the modeling works of autonomous collision avoidance system (ACAS) of unmanned aerial vehicles (UAV). We took and extend the so-called Velocity Obstacle method as the base of the avoidance algorithm, due to its simplicity on handling dynamic environment. The outputs of the method are used to conduct avoidance, which is set as combinations between three modes, i.e., (1) avoid, (2) maintain, and (3) restore. The interactions between the continuous vehicles kinematics and the discrete decision making are described by a hybrid system model. A hybrid automaton is constructed, mapping criteria required for mode changes of the system, including when collisions will occur. To demonstrate algorithm and model performance, several simulations were conducted. This includes scenario where there is just one vehicle avoiding, and where all involved vehicles are avoiding. All simulations were conducted smoothly, resulting in zero collision, even for multiple encounters. Several concluding remarks are presented as a baseline for the research continuation.