Distributed Conflict Detection and Optimal 4D Trajectory Resolution Leveraging Polynomial Based Methods

Authors

Michael Klinefelter, Brigham Young University - ProvoFollow
Austin Stone, Brigham Young UniversityFollow
Joshua Miller, Brigham Young UniversityFollow
Cameron K. Peterson, Brigham Young UniversityFollow
John Salmon, Brigham Young UniversityFollow

Keywords

4D Trajectory, distributed optimization, Conflict Detection and Resolution

Abstract

This paper presents a methodology for distributed conflict detection and resolution of aircraft following time-dependent flight paths. We use parametric fifth-order polynomial splines to define the full, time-based paths of vehicles. This representation can be exploited to rapidly detect conflicts and calculate optimal resolution solutions that minimize deviations from the original path. Conflicts are identified using a Sturm sequencing procedure and resolutions are found using gradient-based optimization techniques. Simulations show the locally optimal resolution of complex multi-vehicle conflicts and large-scale scenarios. Also, a method of fitting the flight path model to data sets is presented and flight path trajectories are shown to accurately represent commercial aircraft trajectories from collected automatic dependent surveillance–broadcast (ADS-B) data sets.

BYU ScholarsArchive Citation

Klinefelter, Michael; Stone, Austin; Miller, Joshua; Peterson, Cameron K.; and Salmon, John, "Distributed Conflict Detection and Optimal 4D Trajectory Resolution Leveraging Polynomial Based Methods" (2024). Student Works. 388.
https://scholarsarchive.byu.edu/studentpub/388

Document Type

Peer-Reviewed Article

Publication Date

2024-05-21

Language

English

College

Ira A. Fulton College of Engineering

Department

Mechanical Engineering

University Standing at Time of Publication

Graduate Student

Copyright Use Information

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