Review: Analysis and Improvement of Traffic Alert and Collision Avoidance System

This paper presents a novel collision avoidance (CA) algorithm for a cooperative fixed-wing unmanned aerial vehicle (UAV). The method is based on maneuver coordination and planned trajectory prediction. Each aircraft in a conflict generates three available maneuvers and predicts the corresponding planned trajectories. The algorithm coordinates planned trajectories between participants in a conflict, determines which combination of planned trajectories provides the best separation, eventually makes an agreement on the maneuver for collision avoidance and activates the preferred maneuvers when a collision is imminent. The emphasis is placed on providing protection for UAVs, while activating maneuvers late enough to reduce interference, which is necessary for collision avoidance in the formation and clustering of UAVs. The CA has been validated with various simulations to show the advantage of collision avoidance for continuous conflicts in multiple, high-dynamic, high-density and three-dimensional (3D) environments. It eliminates the disadvantage of traditional CA, which has high uncertainty, and takes the performance parameters of different aircraft into consideration and makes full use of the maneuverability of fixed-wing aircraft.

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“…According to standard build-up method using dimensionless coefficients, we establish and approximate force and moments. [29]…”

Section: Module Of Trajectory Predictionmentioning

confidence: 99%

“…However, due to the hardware limitation of computing, processing and data transmission, it is The module of trajectory prediction is based on the six-degrees-of-freedom aircraft model. According to standard build-up method using dimensionless coefficients, we establish and approximate force and moments [29].…”

Section: Module Of Threat Managementmentioning

confidence: 99%

Research on the Collision Avoidance Algorithm for Fixed-Wing UAVs Based on Maneuver Coordination and Planned Trajectories Prediction

2019

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“…Review: Analysis and Improvement of Traffic Alert and Collision Avoidance System. [15] A flexible framework for solving the air conflict detection and resolution problem using maximum cliques in a graph. [16]…”

Section: Example Of Research Topicsmentioning

confidence: 99%

Body of Knowledge in Research of Air Traffic Management: Case Study in Indonesi

Ruseno¹,

Sadono

2019

Angkasa

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Air Traffic Management (ATM) is a discipline that manages the movement of flights in the air and on the ground. Its functions are to maintain the safety level required by the authority and to provide the capacity required by the airlines. The challenges in ATM come from the in-balance between the market growth and the available infrastructure and also the gap between the regulations and the technology. The research in ATM provides the solutions by introducing new methods or technologies to cope with those challenges. The effort in organizing and cataloging the Body of Knowledge (BOK) in research of ATM is presented in this report. This BOK is a complete set of research concepts and activities in term of managing the air traffic to improve the air transportation safety and its capacity. Considering the latest publications in the last 5 years, the BOK consists of five areas of operation which are enroute, arrival, terminal, departure and connectivity. Each area of operations consists of several knowledge units that contain several research topics. In this report, a special attention is given to the development of ATM research in Indonesian. It characterizes with the challenges that commonly faced in Indonesia such as high density air traffic, in-sufficient infrastructure/technology, in-balance demand and supply during peak hours and major disruption by natural disasters (volcanoes and earth quakes).The report summarizes that the trend of ATM research in Indonesia is in the knowledge unit of capacity optimization. Additionally, it recommends to explore research activities by implementing new air traffic concepts such as the trajectory based operation and the integrated of departure and arrival management to improve capacity, efficiency and safety.

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“…Technological development has enabled the increase in air traffic density to be mitigated [8,9]. Many studies regarding UAV collision avoidance have been performed in recent years [10][11][12]. CDR and the optimization of different resolutions have been discussed widely by many researchers and practitioners.…”

Section: Introductionmentioning

confidence: 99%

Cooperative Multi-UAV Collision Avoidance Based on a Complex Network

2019

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The conflict resolution problem in cooperative unmanned aerial vehicle (UAV) clusters sharing a three-dimensional airspace with increasing air traffic density is very important. This paper innovatively solves this problem by employing the complex network (CN) algorithm. The proposed approach allows a UAV to perform only one maneuver—that of the flight level change. The novel UAV conflict resolution is divided into two steps, corresponding to the key node selection (KS) algorithm based on the node contraction method and the sense selection (SS) algorithm based on an objective function. The efficiency of the cooperative multi-UAV collision avoidance (CA) system improved a lot due to the simple two-step collision avoidance logic. The paper compares the difference between random selection and the use of the node contraction method to select key nodes. Experiments showed that using the node contraction method to select key nodes can make the collision avoidance effect of UAVs better. The CA maneuver was validated with quantitative simulation experiments, demonstrating advantages such as minimal cost when considering the robustness of the global traffic situation, as well as significant real-time and high efficiency. The CN algorithm requires a relatively small computing time that renders the approach highly suitable for solving real-life operational situations.

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Review: Analysis and Improvement of Traffic Alert and Collision Avoidance System

Cited by 30 publications

References 71 publications

Research on the Collision Avoidance Algorithm for Fixed-Wing UAVs Based on Maneuver Coordination and Planned Trajectories Prediction

Research on the Collision Avoidance Algorithm for Fixed-Wing UAVs Based on Maneuver Coordination and Planned Trajectories Prediction

Body of Knowledge in Research of Air Traffic Management: Case Study in Indonesi

Cooperative Multi-UAV Collision Avoidance Based on a Complex Network

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