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Cooperative sUAV Collision Avoidance Based on Satisficing Theory

  • Namwoo Kim
  • Yoonjin YoonEmail author
Original Paper

Abstract

The recent growth in small unmanned aerial vehicle (sUAV) applications in public and private sectors has generated a greater interest in effective collision avoidance strategies. This paper presents a cooperative collision avoidance approach for sUAV in the low-altitude uncontrolled airspace based on satisficing game theory. By incorporating both the self and cooperative preferences in making individual heading decision, satisficing framework provides a collision avoidance strategy that increases throughput while decreasing unnecessary collisions. A total of 4356 chokepoint scenarios are simulated with varying satisficing parameters, including number of sUAV agents, minimum separation, action angle, and dual utility parameters of raw preference and negotiation index. Simulation-based sensitivity analysis is conducted to find the combined effect of such parameters. The results show that performance of satisficing framework is dependent on traffic density primarily. Except for the very light traffic scenario, the minimum separation and degree of action angle affected the system efficiency the most, while dual utility parameters played crucial roles in highly conflicted scenarios. In conclusion, sUAV traffic and collision rules require an adaptive approach in regard to the traffic density, and satisficing framework can provide an effective collision avoidance strategy in a medium- to high-density traffic environment.

Keywords

Small unmanned aerial vehicles (sUAV) Collision avoidance Satisficing theory UAS traffic management 

Nomenclature

\( U = \left\{ {u_{i} :i = 1,2 \ldots ,N} \right\} \)

Set of N sUAV agents

\( K \)

Detection range

\( R_{\text{s }} \)

Minimum separation

\( O_{i} \)

Origin of \( u_{i} \)

\( D_{i} \)

Destination of \( u_{i} \)

\( \varvec{\varTheta}= \left\{ {\theta :\theta^{o} ,\theta^{ + } ,\theta^{ - } } \right\} \)

Set of action angle, \( \theta^{o} : \) keep current heading, \( \theta^{ + } \): turn right by \( \theta \), \( \theta^{ - } : \) turn left by θ

\( d_{i,j}^{ *} \)

Distance between agents \( u_{i} \) and \( u_{j} \) at their closest approach

\( d_{i,j} \)

Distance between agents \( u_{i} \) and \( u_{j} \)

\( C_{i} = \{ u_{j} : u_{j} \in U, u_{j} \ne u_{i} , d_{i,j} \le K , d_{i,j}^{ *} \le R_{\text{s}} \} \)

Collision set of \( u_{i} \)

\( p\left( {u_{i} } \right) \)

Priority of \( u_{i} \)

\( \gamma \)

Raw preference

\( q \)

Negotiation index

Notes

Acknowledgements

This research was supported in part by Ministry of Land, Infrastructure and Transport of Korean government under Grant 17USTR-B127901-01.

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Copyright information

© The Korean Society for Aeronautical & Space Sciences 2019

Authors and Affiliations

  1. 1.Department of Civil and Environmental EngineeringKorea Advanced Institute of Science and TechnologyDaejeonSouth Korea

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