A Fuzzy Logic Approach for Separation Assurance and Collision Avoidance for Unmanned Aerial SystemsIn the coming years, operations in low altitude airspace will vastly increase as the capabilities and applications of small Unmanned Aerial Systems (sUAS) continue to multiply. Therefore, solutions to managing sUAS in highly congested airspace must be explored. In this study, a Fuzzy Logic based approach was used to help mitigate the risk of collisions between aircraft using separation assurance and collision avoidance techniques. The system was evaluated for its effectiveness to mitigate the risk of mid-air collisions between aircraft. This system utilizes only current state information and can resolve potential conflicts without knowledge of intruder intent. The avoidance logic was verified using formal methods and shown to select the correct action in all instances. Additionally, the Fuzzy Logic Controllers were shown to always turn the vehicles in the correct direction. Numerical testing demonstrated that the avoidance system was able to prevent a mid-air collision between two sUAS in all tested cases. Simulations were also performed in a three-dimensional environment with a heterogenous fleet of sUAS performing a variety of realistic missions. Simulations showed that the system was 99.98 effective at preventing mid-air collisions when separation assurance was disabled (unmitigated case) and 100 effective when enabled (mitigated case).
Document ID
20190027045
Acquisition Source
Ames Research Center
Document Type
Book Chapter
Authors
Cook, Brandon Matthew (NASA Ames Research Center Moffett Field, CA, United States)
Arnett, Timothy (Cincinnati Univ. OH, United States)
Cohen, Kelly (Cincinnati Univ. OH, United States)
Date Acquired
July 8, 2019
Publication Date
July 1, 2017
Publication Information
Publisher: Intech
Subject Category
Air Transportation And Safety
Report/Patent Number
ARC-E-DAA-TN39280Report Number: ARC-E-DAA-TN39280
Distribution Limits
Public
Copyright
Public Use Permitted.
Keywords
Verification & Validation of a Fuzzy Logic ControllerIntelligent ControlUAS Collision Avoidance